4.6 Review

Evaluating the Machine Learning Literature: A Primer and User's Guide for Psychiatrists

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Neurosciences

Deep learning for small and big data in psychiatry

Georgia Koppe et al.

Summary: The article emphasizes the need for psychiatry to utilize modern machine learning techniques, particularly deep learning, to better understand the pathophysiological mechanisms of psychiatric disorders and deliver more effective and personalized treatments. However, the requirement for large training samples poses a challenge as current psychiatric research samples are relatively small, thus hindering the optimal application of these powerful techniques.

NEUROPSYCHOPHARMACOLOGY (2021)

Article Computer Science, Artificial Intelligence

Artificial intelligence and the future of psychiatry: Insights from a global physician survey

P. Murali Doraiswamy et al.

ARTIFICIAL INTELLIGENCE IN MEDICINE (2020)

Review Psychiatry

Big Data Begin in Psychiatry

Myrna M. Weissman

JAMA PSYCHIATRY (2020)

Review Computer Science, Information Systems

Deep learning in clinical natural language processing: a methodical review

Stephen Wu et al.

JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2020)

Article Neurosciences

Machine learning and big data in psychiatry: toward clinical applications

Robb B. Rutledge et al.

CURRENT OPINION IN NEUROBIOLOGY (2019)

Editorial Material Medicine, General & Internal

Reporting of artificial intelligence prediction models

Gary S. Collins et al.

LANCET (2019)

Article Multidisciplinary Sciences

Dissecting racial bias in an algorithm used to manage the health of populations

Ziad Obermeyer et al.

SCIENCE (2019)

Review Behavioral Sciences

Reconciling deep learning with symbolic artificial intelligence: representing objects and relations

Marta Garnelo et al.

CURRENT OPINION IN BEHAVIORAL SCIENCES (2019)

Article Medical Informatics

Comparing different supervised machine learning algorithms for disease prediction

Shahadat Uddin et al.

BMC MEDICAL INFORMATICS AND DECISION MAKING (2019)

Article Health Policy & Services

A Naturalistic Study of Racial Disparities in Diagnoses at an Outpatient Behavioral Health Clinic

Michael A. Gara et al.

PSYCHIATRIC SERVICES (2019)

Review Health Care Sciences & Services

Artificial intelligence, bias and clinical safety

Robert Challen et al.

BMJ QUALITY & SAFETY (2019)

Editorial Material Health Care Sciences & Services

Framing the challenges of artificial intelligence in medicine

Kun-Hsing Yu et al.

BMJ QUALITY & SAFETY (2019)

Article Neurosciences

A Shared Vision for Machine Learning in Neuroscience

Mai-Anh T. Vu et al.

JOURNAL OF NEUROSCIENCE (2018)

Editorial Material Medicine, General & Internal

Time to regenerate: the doctor in the age of artificial intelligence

Xiaoxuan Liu et al.

JOURNAL OF THE ROYAL SOCIETY OF MEDICINE (2018)

Editorial Material Biochemical Research Methods

POINTS OF SIGNIFICANCE Statistics versus machine learning

Danilo Bzdok et al.

NATURE METHODS (2018)

Editorial Material Medicine, General & Internal

Implementing Machine Learning in Health Care - Addressing Ethical Challenges

Danton S. Char et al.

NEW ENGLAND JOURNAL OF MEDICINE (2018)

Review Computer Science, Artificial Intelligence

Ensemble learning: A survey

Omer Sagi et al.

WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY (2018)

Article Computer Science, Interdisciplinary Applications

A comparison of word embeddings for the biomedical natural language processing

Yanshan Wang et al.

JOURNAL OF BIOMEDICAL INFORMATICS (2018)

Editorial Material Medicine, General & Internal

Machine learning in medicine: Addressing ethical challenges

Effy Vayena et al.

PLOS MEDICINE (2018)

Article Biochemistry & Molecular Biology

Resting-state connectivity biomarkers define neurophysiological subtypes of depression

Andrew T. Drysdale et al.

NATURE MEDICINE (2017)

Article Computer Science, Theory & Methods

A simple probabilistic explanation of term frequency-inverse document frequency (tf-idf) heuristic (and variations motivated by this explanation)

Lukas Havrlant et al.

INTERNATIONAL JOURNAL OF GENERAL SYSTEMS (2017)

Review Health Care Sciences & Services

Researching Mental Health Disorders in the Era of Social Media: Systematic Review

Akkapon Wongkoblap et al.

JOURNAL OF MEDICAL INTERNET RESEARCH (2017)

Review Computer Science, Artificial Intelligence

A review of clustering techniques and developments

Amit Saxena et al.

NEUROCOMPUTING (2017)

Review Psychiatry

Text mining applications in psychiatry: a systematic literature review

Adeline Abbe et al.

INTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH (2016)

Article Health Care Sciences & Services

Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View

Wei Luo et al.

JOURNAL OF MEDICAL INTERNET RESEARCH (2016)

Article Psychiatry

Detecting Neuroimaging Biomarkers for Psychiatric Disorders: Sample Size Matters

Hugo G. Schnack et al.

FRONTIERS IN PSYCHIATRY (2016)

Article Psychiatry

Cross-trial prediction of treatment outcome in depression: a machine learning approach

Adam Mourad Chekroud et al.

LANCET PSYCHIATRY (2016)

Article Social Sciences, Interdisciplinary

What makes Big Data, Big Data? Exploring the ontological characteristics of 26 datasets

Rob Kitchin et al.

BIG DATA & SOCIETY (2016)

Article Health Policy & Services

Evaluation of Veterans' Suicide Risk With the Use of Linguistic Detection Methods

Christine Leonard Westgate et al.

PSYCHIATRIC SERVICES (2015)

Review Psychiatry

Big data are coming to psychiatry: a general introduction

Scott Monteith et al.

INTERNATIONAL JOURNAL OF BIPOLAR DISORDERS (2015)

Article Computer Science, Artificial Intelligence

Beyond Manual Tuning of Hyperparameters

Frank Hutter et al.

KUNSTLICHE INTELLIGENZ (2015)

Review Engineering, Biomedical

Machine learning, medical diagnosis, and biomedical engineering research - commentary

Kenneth R. Foster et al.

BIOMEDICAL ENGINEERING ONLINE (2014)

Article Health Care Sciences & Services

Early Experiences With Big Data At An Academic Medical Center

John D. Halamka

HEALTH AFFAIRS (2014)

Article Chemistry, Multidisciplinary

Cross-validation pitfalls when selecting and assessing regression and classification models

Damjan Krstajic et al.

JOURNAL OF CHEMINFORMATICS (2014)

Review Behavioral Sciences

Using Support Vector Machine to identify imaging biomarkers of neurological and psychiatric disease: A critical review

Graziella Orru et al.

NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS (2012)

Review Computer Science, Information Systems

Natural language processing: an introduction

Prakash M. Nadkarni et al.

JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION (2011)

Article Computer Science, Artificial Intelligence

Informing sequential clinical decision-making through reinforcement learning: an empirical study

Susan M. Shortreed et al.

MACHINE LEARNING (2011)

Letter Biochemical Research Methods

Pitfalls of supervised feature selection

Pawel Smialowski et al.

BIOINFORMATICS (2010)

Article Behavioral Sciences

Complacency and Bias in Human Use of Automation: An Attentional Integration

Raja Parasuraman et al.

HUMAN FACTORS (2010)

Article Computer Science, Information Systems

A systematic analysis of performance measures for classification tasks

Marina Sokolova et al.

INFORMATION PROCESSING & MANAGEMENT (2009)

Review Computer Science, Interdisciplinary Applications

Reinforcement Learning: A Tutorial Survey and Recent Advances

Abhijit Gosavi

INFORMS JOURNAL ON COMPUTING (2009)

Editorial Material Multidisciplinary Sciences

Big data: How do your data grow?

Clifford Lynch

NATURE (2008)