Latest AI and machine learning research in primary care for healthcare professionals.
This systematic review aims to assess the effectiveness of AI-Driven Decision Support Systems in improving glycemic control, measured by Time in Range (TIR) and HbA1c levels, in patients with diabetes. Included studies were randomized controlled trials (RCTs) that evaluated AI interventions in diabetes management. Exclusion criteria included non-English studies, non-peer-reviewed articles. Studies...
In recent years Covid-19 impact is causing unprecedented difficulties worldwide, affecting lifestyle choices. The post-pandemic era has made this even more critical.COVID-19 triggers widespread inflammation throughout the body, potentially causing damage to the heart and other vital organs. Mortality data from COVID-19 clearly show that the highest death rates occur in individuals with chronic con...
Although machine learning is frequently used in medicine for predictive purposes, its accuracy in diabetes-related amputation (DRA) remains unclear. F...
BACKGROUND: Breast cancer screening is considered an effective early detection strategy. Artificial intelligence (AI) may both offer benefits and crea...
INTRODUCTION: Risk assessment for high-risk populations is critical for preventing Type 2 Diabetes Mellitus (T2DM). Although China's public health ser...
: This study introduces a novel method for the automated detection and quantification of meibomian gland morphology using gray value distribution prof...
: PSMA PET is essential tool in the management of prostate cancer (PCa) patients in various clinical settings of disease. The tremendous growth of the...
The analysis of blood metabolites may help identify individuals at risk of having COPD and offer insights into its underlying pathophysiology. This st...
RATIONALE: Pulmonary hypertension (PH) poses a significant health threat. Current biomarkers for PH lack specificity and have poor prognostic capabili...
BACKGROUND: Diabetes has emerged as a critical global public health crisis. Prediabetes, as the transitional phase with 5%-10% annual progression to d...
High-content screening (HCS) for bioimaging is a powerful approach to studying biological processes, enabling the acquisition of large amounts of imag...
The study aimed to develop a predictive model using machine learning algorithms, providing healthcare professionals with a novel tool for assessing di...
PURPOSE: In knee osteoarthritis (KOA) treatment, preventive measures to reduce its onset risk are a key factor. Among individuals with radiographicall...
The recent emergence of wearable devices will enable large scale remote brain monitoring. This study investigated whether multimodal wearable sleep re...
Atopic dermatitis (AD) is a chronic, inflammatory skin disorder that affects individuals across the lifespan, with significant implications for both p...
This study presents a web-based interactive health risk prediction tool designed to assess diabetes risk using machine learning models. Built on the...
The comorbidities of hypertension impose a heavy burden on patients and society. Early identification is necessary to prompt intervention, but it re...
The rapid development of microfluidics has driven innovations in material engineering, particularly through its ability to precisely manipulate fluids...
Spinocerebellar ataxia type 2 (SCA2) is an autosomal dominant neurodegenerative disorder marked by cerebellar dysfunction, ataxic gait, and progressiv...
Butyrylcholinesterase (BChE), plays a critical role in alleviating the symptoms of Alzheimer's disease (AD) by regulating acetylcholine levels, emergi...