AIMC Topic: Machine Learning

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Momentary Depression Severity Prediction in Patients With Acute Depression Who Undergo Sleep Deprivation Therapy: Speech-Based Machine Learning Approach.

JMIR mental health
BACKGROUND: Mobile devices for remote monitoring are inevitable tools to support treatment and patient care, especially in recurrent diseases such as major depressive disorder. The aim of this study was to learn if machine learning (ML) models based ...

Machine Learning Driven by Magnetic Resonance Imaging for the Classification of Alzheimer Disease Progression: Systematic Review and Meta-Analysis.

JMIR aging
BACKGROUND: To diagnose Alzheimer disease (AD), individuals are classified according to the severity of their cognitive impairment. There are currently no specific causes or conditions for this disease.

Predicting the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms.

European journal of medical research
BACKGROUND: This study aimed to develop predictive models with robust generalization capabilities for assessing the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms.

Predicting upper limb motor recovery in subacute stroke patients via fNIRS-measured cerebral functional responses induced by robotic training.

Journal of neuroengineering and rehabilitation
BACKGROUND: Neural activation induced by upper extremity robot-assisted training (UE-RAT) helps characterize adaptive changes in the brains of poststroke patients, revealing differences in recovery potential among patients. However, it remains unclea...

Other possible perspectives for solving the negative outcome penalty paradox in the application of artificial intelligence in clinical diagnostics.

Journal of medical ethics
Artificial intelligence (AI), represented by machine learning, artificial neural networks and deep learning, is impacting all areas of medicine, including translational research (from bench to bedside to health policy), clinical medicine (including d...

Machine Learning to Predict the Individual Risk of Treatment-Relevant Toxicity for Patients With Breast Cancer Undergoing Neoadjuvant Systemic Treatment.

JCO clinical cancer informatics
PURPOSE: Toxicity to systemic cancer treatment represents a major anxiety for patients and a challenge to treatment plans. We aimed to develop machine learning algorithms for the upfront prediction of an individual's risk of experiencing treatment-re...

Machine learning mathematical models for incidence estimation during pandemics.

PLoS computational biology
Accurate estimates of the incidence of infectious diseases are key for the control of epidemics. However, healthcare systems are often unable to test the population exhaustively, especially when asymptomatic and paucisymptomatic cases are widespread;...

Predicting the infecting dengue serotype from antibody titre data using machine learning.

PLoS computational biology
The development of a safe and efficacious vaccine that provides immunity against all four dengue virus serotypes is a priority, and a significant challenge for vaccine development has been defining and measuring serotype-specific outcomes and correla...

Integrating machine learning with bioinformatics for predicting idiopathic pulmonary fibrosis prognosis: developing an individualized clinical prediction tool.

Experimental biology and medicine (Maywood, N.J.)
Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial lung disease with a poor prognosis. Its non-specific clinical symptoms make accurate prediction of disease progression challenging. This study aimed to develop molecular-level prognostic m...

Identification and experimental validation of diagnostic and prognostic genes CX3CR1, PID1 and PTGDS in sepsis and ARDS using bulk and single-cell transcriptomic analysis and machine learning.

Frontiers in immunology
BACKGROUND: Sepsis is an uncontrolled reaction to infection that causes severe organ dysfunction and is a primary cause of ARDS. Patients suffering both sepsis and ARDS have a poor prognosis and high mortality. However, the mechanisms behind their si...