AI Medical Compendium Topic

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Cohort Studies

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[Incidence and determinants of viral load rebound in people receiving multi-month dispensing of antiretroviral therapy at the Regional Annex Hospital of Dschang from 2018-2023].

The Pan African medical journal
INTRODUCTION: in Cameroon, multi-month dispensing (MMD) of antiretrovirals (ARVs) was introduced to improve treatment adherence among people living with HIV (PLHIV). However, this strategy has limitations that may lead to viral load rebound. The purp...

Artificial intelligence models predicting abnormal uterine bleeding after COVID-19 vaccination.

Scientific reports
The rapid deployment of COVID-19 vaccines has necessitated the ongoing surveillance of adverse events, with abnormal uterine bleeding (AUB) emerging as a reported concern in vaccinated females. We aimed to develop a machine learning (ML) model to pre...

Shoulder Musculoskeletal Disorder Rehabilitation Using a Robotic Device Based on Electromyography (EMG) Biofeedback: A Retrospective Cohort Study.

Medicina (Kaunas, Lithuania)
: While shoulder injuries represent the musculoskeletal disorders (MSDs) most encountered in physical therapy, there is no consensus on their management. In attempts to provide standardized and personalized treatment, a robotic-assisted device combin...

Machine Learning-Based Prediction of Substance Use in Adolescents in Three Independent Worldwide Cohorts: Algorithm Development and Validation Study.

Journal of medical Internet research
BACKGROUND: To address gaps in global understanding of cultural and social variations, this study used a high-performance machine learning (ML) model to predict adolescent substance use across three national datasets.

Machine learning for the early prediction of long-term cognitive outcome in autoimmune encephalitis.

Journal of psychosomatic research
BACKGROUND AND OBJECTIVE: Autoimmune encephalitis (AE) is an immune-mediated disease. Some patients experience persistent cognitive deficits despite receiving immunotherapy. We aimed to develop a prediction model for long-term cognitive outcomes in p...

Diagnosis of Thyroid Nodule Malignancy Using Peritumoral Region and Artificial Intelligence: Results of Hand-Crafted, Deep Radiomics Features and Radiologists' Assessment in Multicenter Cohorts.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVE: To develop, test, and externally validate a hybrid artificial intelligence (AI) model based on hand-crafted and deep radiomics features extracted from B-mode ultrasound images in differentiating benign and malignant thyroid nodules compare...

Prediction of cognitive conversion within the Alzheimer's disease continuum using deep learning.

Alzheimer's research & therapy
BACKGROUND: Early diagnosis and accurate prognosis of cognitive decline in Alzheimer's disease (AD) is important to timely assignment to optimal treatment modes. We aimed to develop a deep learning model to predict cognitive conversion to guide re-as...

Associations between age, red cell distribution width and 180-day and 1-year mortality in giant cell arteritis patients: mediation analyses and machine learning in a cohort study.

Arthritis research & therapy
OBJECTIVE: The aim of this study was to investigate the correlation between age, red cell distribution width (RDW) levels, and 180-day and 1-year mortality in giant cell arteritis (GCA) patients hospitalized or admitted to the ICU.

Predicting Diagnostic Progression to Schizophrenia or Bipolar Disorder via Machine Learning.

JAMA psychiatry
IMPORTANCE: The diagnosis of schizophrenia and bipolar disorder is often delayed several years despite illness typically emerging in late adolescence or early adulthood, which impedes initiation of targeted treatment.