4.2 Article

Performance Analysis of Conventional Machine Learning Algorithms for Diabetic Sensorimotor Polyneuropathy Severity Classification Using Nerve Conduction Studies

Related references

Note: Only part of the references are listed.
Review Medicine, General & Internal

Early Detection of Diabetic Peripheral Neuropathy: A Focus on Small Nerve Fibres

Jamie Burgess et al.

Summary: Diabetic peripheral neuropathy is a common complication of diabetes that significantly impacts quality of life and healthcare burden. Current screening methods for early detection of DPN have limitations, highlighting the need for further research and clinical practices to improve accuracy and early detection.

DIAGNOSTICS (2021)

Article Medicine, General & Internal

Pharmacological Modulation of Rate-Dependent Depression of the Spinal H-Reflex Predicts Therapeutic Efficacy against Painful Diabetic Neuropathy

Corinne A. Lee-Kubli et al.

Summary: Impaired rate-dependent depression (RDD) of the spinal H-reflex could serve as a biomarker for individuals in whom spinal disinhibition contributes to painful neuropathy, and pharmacological manipulation of RDD can help identify potential therapies against neuropathic pain.

DIAGNOSTICS (2021)

Article Medicine, General & Internal

Performance Analysis of Conventional Machine Learning Algorithms for Identification of Chronic Kidney Disease in Type 1 Diabetes Mellitus Patients

Nakib Hayat Chowdhury et al.

Summary: This study aimed to develop models using machine learning algorithms to quickly predict chronic kidney disease (CKD) in patients with type 1 diabetes mellitus (T1DM) by analyzing 16 years of data from 1375 T1DM patients. The research utilized three data imputation techniques and a resampling technique to preprocess the dataset, applied ten ML algorithms to develop prediction models, and evaluated the models' performance based on various metrics such as accuracy, sensitivity, specificity, and precision. The random forest (RF) classifier model exhibited the best performance for predicting CKD in T1DM patients, followed closely by the LightGBM model, with several other models achieving over 90% accuracy as well.

DIAGNOSTICS (2021)

Article Medicine, General & Internal

Performance Analysis of Conventional Machine Learning Algorithms for Diabetic Sensorimotor Polyneuropathy Severity Classification

Fahmida Haque et al.

Summary: By utilizing machine learning algorithms, particularly the random forest classifier and Michigan Neuropathy Screening Instrument data, the severity of diabetic peripheral neuropathy can be accurately predicted, leading to improved healthcare for diabetic patients.

DIAGNOSTICS (2021)

Article Computer Science, Information Systems

Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms

Arafat Rahman et al.

Summary: The study introduces a novel multimodal biometric system combining EEG and keystroke dynamics, achieving improved accuracy in identification and authentication while also considering anti-spoofing capability. Through the combination of machine learning algorithms, high accuracy biometric recognition is achieved, along with the development of a fast algorithm based on binary template matching.

IEEE ACCESS (2021)

Article Computer Science, Information Systems

Diabetic Sensorimotor Polyneuropathy Severity Classification Using Adaptive Neuro Fuzzy Inference System

Fahmida Haque et al.

Summary: The study aimed to develop an intelligent DSPN severity classifier using ANFIS with MNSI variables and EMG features, achieving high accuracy. The analysis also showed differences in muscle activity during gait among patients with different levels of DSPN severity.

IEEE ACCESS (2021)

Article Computer Science, Information Systems

The Application of the Machine Learning Method in Electromyographic Data

Tao Liu et al.

IEEE ACCESS (2020)

Article Health Care Sciences & Services

Exploring feature selection and classification methods for predicting heart disease

Robinson Spencer et al.

DIGITAL HEALTH (2020)

Article Endocrinology & Metabolism

Risk Factors for Kidney Disease in Type 1 Diabetes

Bruce A. Perkins et al.

DIABETES CARE (2019)

Article Chemistry, Analytical

Wearable Real-Time Heart Attack Detection and Warning System to Reduce Road Accidents

Muhammad E. H. Chowdhury et al.

SENSORS (2019)

Article Chemistry, Analytical

Real-Time Smart-Digital Stethoscope System for Heart Diseases Monitoring

Muhammad E. H. Chowdhury et al.

SENSORS (2019)

Article Computer Science, Artificial Intelligence

Tree-based classifier ensembles for early detection method of diabetes: an exploratory study

Bayu Adhi Tama et al.

ARTIFICIAL INTELLIGENCE REVIEW (2019)

Review Endocrinology & Metabolism

Diagnosing Diabetic Neuropathy: Something Old, Something New

Ioannis N. Petropoulos et al.

DIABETES & METABOLISM JOURNAL (2018)

Editorial Material Endocrinology & Metabolism

Diabetic Neuropathy: A Position Statement by the American Diabetes Association

Rodica Pop-Busui et al.

DIABETES CARE (2017)

Article Endocrinology & Metabolism

A Comparison of Screening Tools for the Early Detection of Peripheral Neuropathy in Adults with and without Type 2 Diabetes

Jennifer J. Brown et al.

JOURNAL OF DIABETES RESEARCH (2017)

Article Biochemical Research Methods

Minimum redundancy maximum relevance feature selection approach for temporal gene expression data

Milos Radovic et al.

BMC BIOINFORMATICS (2017)

Review Endocrinology & Metabolism

Recent Advances in Diagnostic Strategies for Diabetic Peripheral Neuropathy

Jong Chul Won et al.

ENDOCRINOLOGY AND METABOLISM (2016)

Article Endocrinology & Metabolism

Nerve conduction studies in diabetics presymptomatic and symptomatic for diabetic polyneuropathy

Rainha J. de Souza et al.

JOURNAL OF DIABETES AND ITS COMPLICATIONS (2015)

Article Engineering, Biomedical

Effect of diabetic neuropathy severity classified by a fuzzy model in muscle dynamics during gait

Ricky Watari et al.

JOURNAL OF NEUROENGINEERING AND REHABILITATION (2014)

Article Endocrinology & Metabolism

Evaluation of clinical tools and their diagnostic use in distal symmetric polyneuropathy

Kaveh Pourhamidi et al.

PRIMARY CARE DIABETES (2014)

Article Endocrinology & Metabolism

Corneal Confocal Microscopy: A New Technique for Early Detection of Diabetic Neuropathy

N. Papanas et al.

CURRENT DIABETES REPORTS (2013)

Article Endocrinology & Metabolism

Diabetic Neuropathy

Aaron I. Vinik et al.

ENDOCRINOLOGY AND METABOLISM CLINICS OF NORTH AMERICA (2013)

Article Clinical Neurology

Nerve conduction and electromyography studies

N. M. Kane et al.

JOURNAL OF NEUROLOGY (2012)

Article Medical Laboratory Technology

Interrater reliability: the kappa statistic

Mary L. McHugh

BIOCHEMIA MEDICA (2012)

Article Computer Science, Interdisciplinary Applications

Neighborhood Component Feature Selection for High-Dimensional Data

Wei Yang et al.

JOURNAL OF COMPUTERS (2012)

Review Cell Biology

Skin biopsy for the diagnosis of peripheral neuropathy

G. Lauria et al.

HISTOPATHOLOGY (2009)

Article Clinical Neurology

Muscle fiber conduction abnormalities in early diabetic polyneuropathy

J. W. G. Meijer et al.

CLINICAL NEUROPHYSIOLOGY (2008)

Article Health Care Sciences & Services

Selecting indicators for the quality of diabetes care at the health systems level in OECD countries

Antonio Nicolucci et al.

INTERNATIONAL JOURNAL FOR QUALITY IN HEALTH CARE (2006)

Article Clinical Neurology

Comparison of different screening tests for detecting diabetic foot neuropathy

F Forouzandeh et al.

ACTA NEUROLOGICA SCANDINAVICA (2005)

Review Clinical Neurology

Small fiber neuropathy: a common and important clinical disorder

E Hoitsma et al.

JOURNAL OF THE NEUROLOGICAL SCIENCES (2004)