AIMC Topic: Male

Clear Filters Showing 23181 to 23190 of 27433 articles

Resting-state functional MRI metrics to detect freezing of gait in Parkinson's disease: a machine learning approach.

Computers in biology and medicine
Among the symptoms that can occur in Parkinson's disease (PD), Freezing of Gait (FOG) is a disabling phenomenon affecting a large proportion of patients, and it remains not fully understood. Accurate classification of FOG in PD is crucial for tailori...

Fully automated image quality assessment based on deep learning for carotid computed tomography angiography: A multicenter study.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To develop and evaluate the performance of fully automated model based on deep learning and multiple logistics regression algorithm for image quality assessment (IQA) of carotid computed tomography angiography (CTA) images.

Prognostic value of the Glucose-to-Albumin ratio in sepsis-related mortality: A retrospective ICU study.

Diabetes research and clinical practice
AIMS: To investigate the prognostic value of the glucose-to-albumin ratio (GAR) in predicting 30-day and 90-day mortality in septic ICU patients.

A deployment safety case for AI-assisted prostate cancer diagnosis.

Computers in biology and medicine
Deep learning (DL) has the potential to deliver significant clinical benefits. In recent years, an increasing number of DL-based systems have been approved by the relevant regulators, e.g. FDA. Although obtaining regulatory approvals is a prerequisit...

Explainable machine learning for movement disorders - Classification of tremor and myoclonus.

Computers in biology and medicine
BACKGROUND: Treatment for essential tremor (ET) and cortical myoclonus (CM) differs. As their clinical distinction can be difficult, with large inter- and intra-observer variability, there is a need for additional diagnostic tools.

Development and Validation of an Explainable Machine Learning Model for Warning of Hepatitis E Virus-Related Acute Liver Failure.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: Early identification of patients with acute hepatitis E (AHE) who are at high risk of progressing to hepatitis E virus-related acute liver failure (HEV-ALF) is crucial for enabling timely monitoring and intervention. This multice...

A multi-model deep learning approach for the identification of coronary artery calcifications within 2D coronary angiography images.

International journal of computer assisted radiology and surgery
PURPOSE: Identifying and quantifying coronary artery calcification (CAC) is crucial for preoperative planning, as it helps to estimate both the complexity of the 2D coronary angiography (2DCA) procedure and the risk of developing intraoperative compl...

Developments in Digital Wearable in Heart Failure and the Rationale for the Design of TRUE-HF (Ted Rogers Understanding of Exacerbations in Heart Failure) Apple CPET Study.

Circulation. Heart failure
BACKGROUND: Heart failure (HF) is a highly prevalent condition characterized by exercise intolerance, an important metric for ambulatory prognostication. However, current methods to assess exercise capacity are often limited to tertiary HF centers, l...

Multimodal fusion architectures for Alzheimer's disease diagnosis: An experimental study.

Journal of biomedical informatics
OBJECTIVE: In the attempt of early diagnosis of Alzheimer's Disease, varying forms of medical records of multiple modalities are gathered to seize the interaction of multiple factors. However, the heterogeneity of multimodal data brings a challenge. ...

Machine learning models for predicting malnutrition in NICU patients: A comprehensive benchmarking study.

Computers in biology and medicine
Malnutrition, affecting both adults and children globally, results from inadequate nutrient intake or loss of body mass. Traditional screening tools, reliant on detailed questionnaires, are costly, time-consuming, and often lack accuracy and generali...