AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Disease Progression

Showing 321 to 330 of 704 articles

Clear Filters

Investigating the relationship between the SNCA gene and cognitive abilities in idiopathic Parkinson's disease using machine learning.

Scientific reports
Cognitive impairments are prevalent in Parkinson's disease (PD), but the underlying mechanisms of their development are unknown. In this study, we aimed to predict global cognition (GC) in PD with machine learning (ML) using structural neuroimaging, ...

Leveraging electronic health records data to predict multiple sclerosis disease activity.

Annals of clinical and translational neurology
OBJECTIVE: No relapse risk prediction tool is currently available to guide treatment selection for multiple sclerosis (MS). Leveraging electronic health record (EHR) data readily available at the point of care, we developed a clinical tool for predic...

Early risk assessment for COVID-19 patients from emergency department data using machine learning.

Scientific reports
Since its emergence in late 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic with more than 55 million reported cases and 1.3 million estimated deaths worldwide. While epidemiological and clinical character...

Predicting COVID-19 disease progression and patient outcomes based on temporal deep learning.

BMC medical informatics and decision making
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has caused health concerns worldwide since December 2019. From the beginning of infection, patients will progress through different symptom stages, such as fever, dyspnea or even death. Ide...

Screening of Alzheimer's disease by facial complexion using artificial intelligence.

Aging
Despite the increasing incidence and high morbidity associated with dementia, a simple, non-invasive, and inexpensive method of screening for dementia is yet to be discovered. This study aimed to examine whether artificial intelligence (AI) could dis...

An Interpretable Machine Learning Survival Model for Predicting Long-term Kidney Outcomes in IgA Nephropathy.

AMIA ... Annual Symposium proceedings. AMIA Symposium
IgA nephropathy (IgAN) is common worldwide and has heterogeneous phenotypes. Predicting long-term outcomes is important for clinical decision-making. As right-censored patients become common during the long-term follow-up, either excluding these pati...

Cognitive and MRI trajectories for prediction of Alzheimer's disease.

Scientific reports
The concept of Mild Cognitive Impairment (MCI) is used to describe the early stages of Alzheimer's disease (AD), and identification and treatment before further decline is an important clinical task. We selected longitudinal data from the ADNI databa...

Current cancer driver variant predictors learn to recognize driver genes instead of functional variants.

BMC biology
BACKGROUND: Identifying variants that drive tumor progression (driver variants) and distinguishing these from variants that are a byproduct of the uncontrolled cell growth in cancer (passenger variants) is a crucial step for understanding tumorigenes...

Modular machine learning for Alzheimer's disease classification from retinal vasculature.

Scientific reports
Alzheimer's disease is the leading cause of dementia. The long progression period in Alzheimer's disease provides a possibility for patients to get early treatment by having routine screenings. However, current clinical diagnostic imaging tools do no...