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Artificial intelligence for biomarker discovery in Alzheimer's disease and dementia

ALZHEIMERS & DEMENTIA (2023)

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Article Neurosciences

Comparison of Machine Learning-based Approaches to Predict the Conversion to Alzheimer?s Disease from Mild Cognitive Impairment

Raffaella Franciotti et al.

Summary: By comparing the prognostic performances of three supervised machine learning algorithms using multimodal biomarkers, this study found that combining clinical and biological measures can improve the accuracy of predicting conversion from mild cognitive impairment (MCI) to Alzheimer's disease. The results also revealed that neuropsychological test scores, neuroimaging data, and protein measurements are important variables for accurate prediction.

NEUROSCIENCE (2023)

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Review Ophthalmology

Ocular Biomarkers for Alzheimer Disease Dementia An Umbrella Review of Systematic Reviews and Meta-analyses

Eliana Costanzo et al.

Summary: This study performed an umbrella review of systematic reviews to assess the diagnostic accuracy of ocular biomarkers for the early diagnosis of Alzheimer disease. The results showed that parameters such as peripapillary retinal nerve fiber layer thickness, foveal avascular zone, and saccadic eye movements prosaccade latency had the most evidence for detecting AD compared with healthy controls.

JAMA OPHTHALMOLOGY (2023)

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Review Clinical Neurology

Increasing participant diversity in AD research: Plans for digital screening, blood testing, and a community-engaged approach in the Alzheimer's Disease Neuroimaging Initiative 4

Michael W. Weiner et al.

Summary: ADNI4 aims to improve the validation of biomarkers for Alzheimer's disease clinical trials using new technologies and community-engaged approaches to recruit participants from underrepresented populations. The study will utilize an online portal for screening and conduct blood and digital cognitive testing. Additionally, MRI sequences and new PET tracers will be added to the project.

ALZHEIMERS & DEMENTIA (2023)

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Review Biochemistry & Molecular Biology

Status of Metabolomic Measurement for Insights in Alzheimer's Disease Progression-What Is Missing?

Chunyuan Yin et al.

Summary: Alzheimer's disease is an aging-related neurodegenerative disease that leads to progressive memory loss and cognitive decline. Understanding the pathogenesis and etiology of the disease is still limited, and there are no effective treatments available. Metabolomics offers a valuable approach to studying biochemical changes and discovering potential therapeutic targets.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2023)

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Review Neurosciences

Plasma phospho-tau in Alzheimer's disease: towards diagnostic and therapeutic trial applications

Fernando Gonzalez-Ortiz et al.

Summary: Alzheimer's disease is a major burden on individuals, families, caregivers, and healthcare systems. Practicality and accessibility challenges hinder the widespread availability of biomarker-supported diagnosis, resulting in many undiagnosed cases. Blood biomarker, such as plasma phosphorylated tau (p-tau), shows promise in expanding access to AD diagnostics and informing clinical diagnosis and eligibility for therapies.

MOLECULAR NEURODEGENERATION (2023)

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Article Cell Biology

Blood biomarkers for Alzheimer's disease in clinical practice and trials

Oskar Hansson et al.

Summary: Blood-based biomarkers have the potential to greatly improve the diagnosis and prognosis of Alzheimer's disease (AD) in clinical practice. Assays for measuring phosphorylated tau (p-tau) in plasma have high diagnostic accuracy in distinguishing AD from other neurodegenerative diseases in patients with cognitive impairment. These biomarkers can also predict the future development of AD dementia in patients with mild cognitive complaints. The use of such blood-based biomarkers can reduce the need for more costly investigations and facilitate identification of individuals with pre-symptomatic AD in clinical trials.

NATURE AGING (2023)

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Editorial Material Pharmacology & Pharmacy

Blood-Based Alzheimer's Biomarkers

[Anonymous]

CLINICAL PHARMACOLOGY & THERAPEUTICS (2022)

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Review Genetics & Heredity

Navigating the pitfalls of applying machine learning in genomics

Sean Whalen et al.

Summary: This review discusses common pitfalls encountered when applying supervised machine learning in genomics, emphasizing how the structure of genomics data can bias performance evaluations and predictions. It also presents solutions and appropriate use cases to address the challenges associated with applying cutting-edge ML methods to genomics.

NATURE REVIEWS GENETICS (2022)

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Review Radiology, Nuclear Medicine & Medical Imaging

Quantification of amyloid PET for future clinical use: a state-of-the-art review

Hugh G. Pemberton et al.

Summary: This article summarizes and discusses several tools and measures available for amyloid PET quantification, highlighting the importance of quantitative measurement in early diagnosis and treatment response monitoring.

EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING (2022)

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Review Biochemistry & Molecular Biology

Biomarkers for the Diagnosis of Alzheimer's Disease in Clinical Practice: The Role of CSF Biomarkers during the Evolution of Diagnostic Criteria

Maciej Dulewicz et al.

Summary: Alzheimer's disease is a common cause of dementia and early diagnosis is challenging. CSF biomarkers can detect neuropathological changes before the development of AD and improve clinical diagnosis accuracy. Technological advances and expert recommendations may lead to wider use of these diagnostic tests in clinical practice.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2022)

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Article Multidisciplinary Sciences

Deep learning methods to predict amyotrophic lateral sclerosis disease progression

Corrado Pancotti et al.

Summary: This study investigated how deep learning models perform in predicting ALS progression using the PRO-ACT data. It found that deep learning models showed comparable or better performance with respect to the state-of-the-art models in predicting ALS disease progression, representing a valid alternative.

SCIENTIFIC REPORTS (2022)

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Article Computer Science, Artificial Intelligence

Deep Neural Networks and Tabular Data: A Survey

Vadim Borisov et al.

Summary: This work provides an overview of state-of-the-art deep learning methods for tabular data, covering data transformations, specialized architectures, and regularization models. It also discusses deep learning approaches for generating tabular data and strategies for explaining deep models on tabular data. The results suggest that gradient-boosted tree ensembles still outperform deep learning models on supervised learning tasks for tabular data, indicating a stagnation in the research progress of competitive deep learning models in this area. This study serves as a valuable starting point for researchers and practitioners interested in deep learning with tabular data.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2022)

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Article Biochemistry & Molecular Biology

Multi-task deep autoencoder to predict Alzheimer's disease progression using temporal DNA methylation data in peripheral blood

Li Chen et al.

Summary: Traditional approaches for diagnosing Alzheimer's disease (AD) are invasive and expensive. In this study, the researchers developed two multi-task deep autoencoders to predict AD progression and reconstruct DNA methylation profiles using peripheral blood samples. The proposed method outperforms existing machine learning approaches and shows promising results.

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL (2022)

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Review Clinical Neurology

Blood-based biomarkers for Alzheimer's disease: towards clinical implementation

Charlotte E. Teunissen et al.

Summary: Recent research suggests that blood-based biomarkers for Alzheimer's disease may become a reality, with consistent results across different cohorts. Additionally, other blood-based biomarkers can provide information about disease progression and treatment effects.

LANCET NEUROLOGY (2022)

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Article Biochemistry & Molecular Biology

Diagnostic performance and prediction of clinical progression of plasma phospho-tau181 in the Alzheimer's Disease Neuroimaging Initiative

Thomas K. Karikari et al.

Summary: Plasma phosphorylated-tau181 (p-tau181) is a promising blood-based biomarker specific for Alzheimer's disease (AD), showing high diagnostic accuracy and increasing levels with disease progression.

MOLECULAR PSYCHIATRY (2021)

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Review Ophthalmology

Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective

Ji-Peng Olivia Li et al.

Summary: The simultaneous maturation of multiple digital and telecommunications technologies in 2020 has created an unprecedented opportunity for ophthalmology to adapt to new models of care using tele-health supported by digital innovations. Various countries are utilizing digital innovations to tackle eye diseases and discussing the impact of COVID-19 on global eye care services.

PROGRESS IN RETINAL AND EYE RESEARCH (2021)

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Review Biochemistry & Molecular Biology

Machine Learning and Novel Biomarkers for the Diagnosis of Alzheimer's Disease

Chun-Hung Chang et al.

Summary: This study investigated the application of machine learning and novel biomarkers in the diagnosis of Alzheimer's disease (AD). In addition to traditional Aβ and tau-related biomarkers, biomarkers related to neuronal injury, synaptic dysfunction, and neuroinflammation were explored. Machine learning combined with novel biomarkers and multiple variables may improve the sensitivity and specificity in diagnosing AD.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2021)

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Article Multidisciplinary Sciences

Resting state EEG biomarkers of cognitive decline associated with Alzheimer's disease and mild cognitive impairment

Amir H. Meghdadi et al.

Summary: This study explored the utility of EEG measures as potential biomarkers for cognitive decline in AD and MCI, identifying increases in slow frequency power and coherence in AD, and proposing a novel Power Distribution Distance Measure (PDDM) to differentiate AD and MCI patients. The increase in slow frequency power opposed that of normal aging, while the decrease in Alpha band power in AD paralleled normal aging effects. The proposed PDDM showed enhanced significance and effect size in distinguishing MCI, with classifications achieving AUC = 0.85 for AD and AUC = 0.6 for MCI after cross-validation.

PLOS ONE (2021)

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Article Multidisciplinary Sciences

A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer's disease

Shaker El-Sappagh et al.

Summary: Research on Alzheimer's disease diagnosis and progression detection often relies on single modality, treats diagnosis and progression detection as separate problems, and overlooks the explainability of complex machine learning models, leading to difficulties in clinical practice and physician trust.

SCIENTIFIC REPORTS (2021)

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Article Clinical Neurology

Associations of Plasma Phospho-Tau217 Levels With Tau Positron Emission Tomography in Early Alzheimer Disease

Shorena Janelidze et al.

Summary: This study highlights the potential of plasma P-tau217 as an early biomarker for Alzheimer's disease, showing elevated levels before tau-PET detected insoluble tau aggregates. Modeling suggests that changes in plasma and CSF P-tau217 precede tau-PET signals, indicating its usefulness in detecting early AD brain pathology.

JAMA NEUROLOGY (2021)

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Review Clinical Neurology

Modifiable risk factors for dementia and dementia risk profiling. A user manual for Brain Health Services-part 2 of 6

Janice M. Ranson et al.

Summary: The article discusses the development of new Brain Health Services for dementia prevention, emphasizing risk analysis and personalized risk reduction interventions. It suggests selecting appropriate risk assessment tools based on age and risk level, while considering modifiable risk factors.

ALZHEIMERS RESEARCH & THERAPY (2021)

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Review Medicine, General & Internal

Biomarker discovery studies for patient stratification using machine learning analysis of omics data: a scoping review

Enrico Glaab et al.

Summary: The review analyzed biomarker discovery studies using omics data for patient stratification that led to clinically validated FDA-cleared tests or laboratory developed tests. Common characteristics identified included methodological and practical features such as study design choices, technology combinations, integration of biological knowledge, strict criteria, and suitable statistical and machine learning methods. Successful models in personalized oncology have paved the way for potential applications in non-cancer diseases, showing the efficacy of multivariate omics biomarker design for complex disorders.

BMJ OPEN (2021)

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Article Biochemistry & Molecular Biology

Four distinct trajectories of tau deposition identified in Alzheimer's disease

Jacob W. Vogel et al.

Summary: By using an unbiased subtyping algorithm, the study systematically characterized longitudinal tau variability in human Alzheimer's disease, identifying four trajectories of tau deposition with distinct clinical features. The results suggest that variation in tau pathology is common and systematic, potentially necessitating a re-examination of the notion of 'typical AD' and a revisiting of tau pathological staging.

NATURE MEDICINE (2021)

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Review Neurosciences

Aging brain mechanics: Progress and promise of magnetic resonance elastography

Lucy Hiscox et al.

Summary: Neuroimaging techniques like magnetic resonance elastography play a crucial role in characterizing healthy brain aging and early detection of neurodegenerative diseases. The viscoelasticity of brain tissue provides a unique biophysical signature of neuroanatomy, reflecting the composition and organization of tissue microstructure. Advancements in brain MRE technology offer valuable insights into brain aging, neurodegeneration, and structure-function relationships, with potential to serve as an imaging biomarker for neurodegenerative conditions.

NEUROIMAGE (2021)

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Editorial Material Multidisciplinary Sciences

Personalized profiles for disease risk must capture all facets of health

Mark McCarthy et al.

NATURE (2021)

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Review Biochemistry & Molecular Biology

Biomarkers for neurodegenerative diseases

Oskar Hansson

Summary: Biomarkers for neurodegenerative diseases play a crucial role in improving diagnostic workup and therapy monitoring, with emerging blood-based markers and discussions on their implementation in clinical practice and trials.

NATURE MEDICINE (2021)

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Article Biochemistry & Molecular Biology

Prediction of future Alzheimer's disease dementia using plasma phospho-tau combined with other accessible measures

Sebastian Palmqvist et al.

Summary: Plasma P-tau, in combination with plasma phospho-tau and other biomarkers, along with clinical tests and APOE genotyping, can accurately predict the risk of Alzheimer's disease dementia, improving diagnostic prediction and facilitating recruitment for clinical trials.

NATURE MEDICINE (2021)

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Article Multidisciplinary Sciences

Molecular subtyping of Alzheimer's disease with consensus non-negative matrix factorization

Chunlei Zheng et al.

Summary: Utilizing gene expression data, two molecular subtypes of AD were identified: synaptic type and inflammatory type. These subtypes are associated with APOE genotypes and gender, and have potential implications in disease mechanism understanding, clinical trial design, drug discovery, and precision medicine for AD.

PLOS ONE (2021)

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Article Multidisciplinary Sciences

Identifying individuals with high risk of Alzheimer's disease using polygenic risk scores

Ganna Leonenko et al.

Summary: Polygenic Risk Scores for Alzheimer's disease offer unique possibilities for reliably identifying individuals at high and low risk. The study shows that the best prediction accuracy is achieved with a model including APOE and a polygenic score excluding APOE. Standardizing PRS against the population mean makes individuals' scores comparable between studies.

NATURE COMMUNICATIONS (2021)

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Article Multidisciplinary Sciences

A multicentre validation study of the diagnostic value of plasma neurofilament light

Nicholas J. Ashton et al.

Nature Communications (2021)

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Article Medicine, General & Internal

Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence

Gary S. Collins et al.

Summary: This paper outlines the development process of TRIPOD-AI and PROBAST-AI, including systematic reviews, Delphi process, virtual consensus meetings, and tool development, in five stages. The aim is to provide reporting guidelines and a standardized tool for the critical appraisal of machine learning based prediction model studies.

BMJ OPEN (2021)

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Article Clinical Neurology

Synaptic density in carriers of C9orf72 mutations: a [11C] UCB-J PET study

Maura Malpetti et al.

Summary: Research shows that pre-symptomatic carriers of C9orf72 mutation exhibit reduced synaptic density in the thalamus compared to controls, and there is extensive synaptic loss in the frontal temporal regions of symptomatic patients with frontotemporal dementia. Therefore, the use of [C-11]UCB-J PET may aid in early assessment, monitoring of disease progression, and evaluation of new preventive treatment strategies.

ANNALS OF CLINICAL AND TRANSLATIONAL NEUROLOGY (2021)

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Article Clinical Neurology

Feasibility study for detection of retinal amyloid in clinical trials: The Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) trial

Jennifer Ngolab et al.

Summary: The study compared retinal and cerebral amyloid deposits in clinically normal individuals with high and low amyloid levels. It found a greater number of retinal spots in individuals with high amyloid levels, and a positive correlation between retinal spots and brain amyloid. Larger sample sizes are needed to fully understand the relationship between amyloid PET and retinal amyloid deposition.

ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING (2021)

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Article Neuroimaging

Open science datasets from PREVENT-AD, a longitudinal cohort of pre-symptomatic Alzheimer's disease

Jennifer Tremblay-Mercier et al.

Summary: The creation of an open science dataset from the PREVENT-AD cohort has allowed for the sharing of longitudinal imaging and other information related to AD with the global research community. This living resource not only facilitates continued data acquisition, but also offers opportunities to enhance the understanding of AD pathogenesis.

NEUROIMAGE-CLINICAL (2021)

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Article Clinical Neurology

Three plasma metabolites in elderly patients differentiate mild cognitive impairment and Alzheimer's disease: a pilot study

Alana C. Costa et al.

EUROPEAN ARCHIVES OF PSYCHIATRY AND CLINICAL NEUROSCIENCE (2020)

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Article Clinical Neurology

Cerebro-spinal fluid biomarker levels: phosphorylated tau (T) and total tau (N) as markers for rate of progression in Alzheimer's disease

Carina Wattmo et al.

BMC NEUROLOGY (2020)

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Review Clinical Neurology

A multiomics approach to heterogeneity in Alzheimer's disease: focused review and roadmap

AmanPreet Badhwar et al.

BRAIN (2020)

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Article Clinical Neurology

Plasma tau, neurofilament light chain and amyloid-beta levels and risk of dementia; a population-based cohort study

Frank de Wolfa et al.

BRAIN (2020)

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Review Behavioral Sciences

How to do things with (thousands of) words: Computational approaches to discourse analysis in Alzheimer's disease

Natasha Clarke et al.

CORTEX (2020)

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Article Neurosciences

Using Machine Learning to Predict Dementia from Neuropsychiatric Symptom and Neuroimaging Data

Sascha Gill et al.

JOURNAL OF ALZHEIMERS DISEASE (2020)

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Article Multidisciplinary Sciences

Relationship between dementia and gut microbiome-associated metabolites: a cross-sectional study in Japan

Naoki Saji et al.

SCIENTIFIC REPORTS (2020)

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Article Computer Science, Artificial Intelligence

The reliability of a deep learning model in clinical out-of-distribution MRI data: A multicohort study

Gustav Martensson et al.

MEDICAL IMAGE ANALYSIS (2020)

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Review Clinical Neurology

An update on blood-based biomarkers for non-Alzheimer neurodegenerative disorders

Nicholas J. Ashton et al.

NATURE REVIEWS NEUROLOGY (2020)

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Review Biochemical Research Methods

A comprehensive systematic review of CSF proteins and peptides that define Alzheimer's disease

Cristina M. Pedrero-Prieto et al.

CLINICAL PROTEOMICS (2020)

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Review Health Care Sciences & Services

Neurophysiological Hallmarks of Neurodegenerative Cognitive Decline: The Study of Brain Connectivity as a Biomarker of Early Dementia

Paolo Maria Rossini et al.

JOURNAL OF PERSONALIZED MEDICINE (2020)

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Article Biochemistry & Molecular Biology

Proteome profiling in cerebrospinal fluid reveals novel biomarkers of Alzheimer's disease

Jakob M. Bader et al.

MOLECULAR SYSTEMS BIOLOGY (2020)

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Review Clinical Neurology

Applications of machine learning to diagnosis and treatment of neurodegenerative diseases

Monika A. Myszczynska et al.

NATURE REVIEWS NEUROLOGY (2020)

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Review Behavioral Sciences

Artificial intelligence and neuropsychological measures: The case of Alzheimer's disease

Petronilla Battista et al.

NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS (2020)

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Article Multidisciplinary Sciences

Inexpensive, non-invasive biomarkers predict Alzheimer transition using machine learning analysis of the Alzheimer's Disease Neuroimaging (ADNI) database

Juan Felipe Beltran et al.

PLOS ONE (2020)

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Article Multidisciplinary Sciences

Gene biomarker discovery at different stages of Alzheimer using gene co-expression network approach

Negar Sadat Soleimani Zakeri et al.

SCIENTIFIC REPORTS (2020)

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Article Clinical Neurology

Identification of potential blood biomarkers for early diagnosis of Alzheimer's disease through RNA sequencing analysis

Daichi Shigemizu et al.

ALZHEIMERS RESEARCH & THERAPY (2020)

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Article Multidisciplinary Sciences

Blood biomarkers indicate that the preclinical stages of Alzheimer's disease present overlapping molecular features

Alfonso Di Costanzo et al.

SCIENTIFIC REPORTS (2020)

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Article Clinical Neurology

Comparing fluid biomarkers of Alzheimer's disease between African American or Black African and white groups: A systematic review and meta-analysis

Aiysha Chaudhry et al.

JOURNAL OF THE NEUROLOGICAL SCIENCES (2020)

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Article Clinical Neurology

Inclusion of ethnoracial populations and diversity remains a key challenge in Alzheimer's disease biofluid-based biomarker studies

Ganesh M. Babulal

JOURNAL OF THE NEUROLOGICAL SCIENCES (2020)

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A comparison of machine learning methods for survival analysis of high-dimensional clinical data for dementia prediction

Annette Spooner et al.

SCIENTIFIC REPORTS (2020)

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Article Health Care Sciences & Services

A semi-supervised approach for rapidly creating clinical biomarker phenotypes in the UK Biobank using different primary care EHR and clinical terminology systems

Spiros Denaxas et al.

JAMIA OPEN (2020)

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Article Health Care Sciences & Services

The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database

Stan Benjamens et al.

NPJ DIGITAL MEDICINE (2020)

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Article Neuroimaging

Modelling prognostic trajectories of cognitive decline due to Alzheimer's disease

Joseph Giorgio et al.

NEUROIMAGE-CLINICAL (2020)

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Review Biochemistry & Molecular Biology

Artificial intelligence (AI) and big data in cancer and precision oncology

Zodwa Dlamini et al.

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL (2020)

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Article Computer Science, Artificial Intelligence

Not-so-supervised: A survey of semi-supervised, multi-instance, and transfer learning in medical image analysis

Veronika Cheplygina et al.

MEDICAL IMAGE ANALYSIS (2019)

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Article Genetics & Heredity

Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing

Brian W. Kunkle et al.

NATURE GENETICS (2019)

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Article Multidisciplinary Sciences

Predicting Alzheimer's disease progression using multi-modal deep learning approach

Garam Lee et al.

SCIENTIFIC REPORTS (2019)

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Article Medicine, General & Internal

Deep and Frequent Phenotyping study protocol: an observational study in prodromal Alzheimer's disease

Ivan Koychev et al.

BMJ OPEN (2019)

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Article Clinical Neurology

A metabolomic approach to identifying biomarkers in blood of Alzheimer's disease

Chia-Ni Lin et al.

ANNALS OF CLINICAL AND TRANSLATIONAL NEUROLOGY (2019)

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Review Neurosciences

Neuroimaging Biomarkers for Alzheimer's Disease

Freddie Marquez et al.

MOLECULAR NEURODEGENERATION (2019)

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Editorial Material Pharmacology & Pharmacy

Therapeutics for dementia and Alzheimer's disease: New directions for precision medicine

J. A. Duce et al.

BRITISH JOURNAL OF PHARMACOLOGY (2019)

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Editorial Material Dermatology

Research Techniques Made Simple: Feature Selection for Biomarker Discovery

Rodrigo Torres et al.

JOURNAL OF INVESTIGATIVE DERMATOLOGY (2019)

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Article Geriatrics & Gerontology

Biomarker-guided clustering of Alzheimer's disease clinical syndromes

Nicola Toschi et al.

NEUROBIOLOGY OF AGING (2019)

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Article Mathematical & Computational Biology

Prediction and Classification of Alzheimer's Disease Based on Combined Features From Apolipoprotein-E Genotype, Cerebrospinal Fluid, MR, and FDG-PET Imaging Biomarkers

Yubraj Gupta et al.

FRONTIERS IN COMPUTATIONAL NEUROSCIENCE (2019)

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Review Geriatrics & Gerontology

Methodological Issues in the Clinical Validation of Biomarkers for Alzheimer's Disease: The Paradigmatic Example of CSF

Marco Canevelli et al.

FRONTIERS IN AGING NEUROSCIENCE (2019)

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Review Ophthalmology

Artificial intelligence and deep learning in ophthalmology

Daniel Shu Wei Ting et al.

BRITISH JOURNAL OF OPHTHALMOLOGY (2019)

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Article Biochemistry & Molecular Biology

Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer's disease

Oliver Preische et al.

NATURE MEDICINE (2019)

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Review Health Care Sciences & Services

Digital biomarkers for Alzheimer's disease: the mobile/wearable devices opportunity

Lampros C. Kourtis et al.

NPJ DIGITAL MEDICINE (2019)

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Review Biochemical Research Methods

Improving PET Imaging Acquisition and Analysis With Machine Learning: A Narrative Review With Focus on Alzheimer's Disease and Oncology

Ian R. Duffy et al.

MOLECULAR IMAGING (2019)

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Review Clinical Neurology

Salivary Biomarkers for Alzheimer's Disease and Related Disorders

Nicholas J. Ashton et al.

NEUROLOGY AND THERAPY (2019)

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Article Clinical Neurology

A metabolite-based machine learning approach to diagnose Alzheimer-type dementia in blood: Results from the European Medical Information Framework for Alzheimer disease biomarker discovery cohort

Daniel Stamate et al.

ALZHEIMERS & DEMENTIA-TRANSLATIONAL RESEARCH & CLINICAL INTERVENTIONS (2019)

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Editorial Material Geriatrics & Gerontology

The role of biomarkers and imaging in the clinical diagnosis of dementia

Antony J. Bayer

AGE AND AGEING (2018)

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Biomarker definitions and their applications

Robert M. Califf

EXPERIMENTAL BIOLOGY AND MEDICINE (2018)

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Urine-Based Biomarkers for Alzheimer's Disease Identified Through Coupling Computational and Experimental Methods

Fang Yao et al.

JOURNAL OF ALZHEIMERS DISEASE (2018)

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Methodologic Guide for Evaluating Clinical Performance and Effect of Artificial Intelligence Technology for Medical Diagnosis and Prediction

Seong Ho Park et al.

RADIOLOGY (2018)

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Neurocognitive disorders in ICD-11: the debate and its outcome

Wolfgang Gaebel et al.

WORLD PSYCHIATRY (2018)

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Article Medicine, General & Internal

Brain and blood metabolite signatures of pathology and progression in Alzheimer disease: A targeted metabolomics study

Vijay R. Varma et al.

PLOS MEDICINE (2018)

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Article Neuroimaging

Combining viscoelasticity, diffusivity and volume of the hippocampus for the diagnosis of Alzheimer's disease based on magnetic resonance imaging

Lea M. Gerischer et al.

NEUROIMAGE-CLINICAL (2018)

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Article Biochemistry & Molecular Biology

An Artificial Neural Network Integrated Pipeline for Biomarker Discovery Using Alzheimer's Disease as a Case Study

Dimitrios Zafeiris et al.

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL (2018)

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Article Biochemistry & Molecular Biology

Clinically applicable deep learning for diagnosis and referral in retinal disease

Jeffrey De Fauw et al.

NATURE MEDICINE (2018)

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Article Public, Environmental & Occupational Health

Phenotypic Heterogeneity in Dementia: A Challenge for Epidemiology and Biomarker Studies

Joanne Ryan et al.

FRONTIERS IN PUBLIC HEALTH (2018)

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Article Geriatrics & Gerontology

Clinical validity of cerebrospinal fluid Aβ42, tau, and phospho-tau as biomarkers for Alzheimer's disease in the context of a structured 5-phase development framework

Niklas Mattsson et al.

NEUROBIOLOGY OF AGING (2017)

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Article Clinical Neurology

Association of Dual-Task Gait With Incident Dementia in Mild Cognitive Impairment Results From the Gait and Brain Study

Manuel M. Montero-Odasso et al.

JAMA NEUROLOGY (2017)

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Article Neuroimaging

Selection bias in the reported performances of AD classification pipelines

Alex F. Mendelson et al.

NEUROIMAGE-CLINICAL (2017)

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Article Clinical Neurology

Association of amine biomarkers with incident dementia and Alzheimer's disease in the Framingham Study

Vincent Chouraki et al.

ALZHEIMERS & DEMENTIA (2017)

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Imaging plus X: multimodal models of neurodegenerative disease

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A Review of Fluid Biomarkers for Alzheimer's Disease: Moving from CSF to Blood

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Review Neurosciences

Sleep: A Novel Mechanistic Pathway, Biomarker, and Treatment Target in the Pathology of Alzheimer's Disease?

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Changes in the Chemical Barrier Composition of Tears in Alzheimer's Disease Reveal Potential Tear Diagnostic Biomarkers

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PLOS ONE (2016)

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Common polygenic variation enhances risk prediction for Alzheimer's disease

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BRAIN (2015)

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VALUE IN HEALTH (2015)

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DEMENTIA AND GERIATRIC COGNITIVE DISORDERS (2014)

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Mild Cognitive Impairment and Mild Dementia: A Clinical Perspective

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MAYO CLINIC PROCEEDINGS (2014)

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Characterization of Atrophic Changes in the Cerebral Cortex Using Fractal Dimensional Analysis

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CSF phosphorylated tau in the diagnosis and prognosis of mild cognitive impairment and Alzheimer's disease: a meta-analysis of 51 studies

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The uniform data set (UDS): Clinical and cognitive variables and descriptive data from Alzheimer disease centers

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CSF Aβ 42 levels correlate with amyloid-neuropathology in a population-based autopsy study

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