Primary Care

Enhancing neurological disease diagnostics: fusion of deep transfer learning with optimization algorithm for acute brain stroke prediction using facial images.

Stroke is a main risk to life and fitness in current society, particularly in the aging population. Also, the stroke is recognized as a cerebrovascular accident. It contains a nervous illness, which can result from haemorrhage or ischemia of the brain veins, and regular mains to assorted motor and cognitive damages that cooperate with functionality. Screening for stroke comprises physical examinat...

Application of an interpretable machine learning method to predict the risk of death during hospitalization in patients with acute myocardial infarction combined with diabetes mellitus.

BACKGROUND: Predicting the prognosis of patients with acute myocardial infarction (AMI) combined with diabetes mellitus (DM) is crucial due to high in-hospital mortality rates. This study aims to develop and validate a mortality risk prediction model for these patients by interpretable machine learning (ML) methods.

Artificial Intelligence in Dentistry: A Narrative Review of Diagnostic and Therapeutic Applications.

Advancements in digital and precision medicine have fostered the rapid development of artificial intelligence (AI) applications, including machine lea...

NA_mCNN: Classification of Sodium Transporters in Membrane Proteins by Integrating Multi-Window Deep Learning and ProtTrans for Their Therapeutic Potential.

Sodium transporters maintain cellular homeostasis by transporting ions, minerals, and nutrients across the membrane, and Na+/K+ ATPases facilitate the...

Transformer-based deep learning ensemble framework predicts autism spectrum disorder using health administrative and birth registry data.

Early diagnosis and access to resources, support and therapy are critical for improving long-term outcomes for children with autism spectrum disorder ...

Virtual lung screening trial (VLST): An in silico study inspired by the national lung screening trial for lung cancer detection.

Clinical imaging trials play a crucial role in advancing medical innovation but are often costly, inefficient, and ethically constrained. Virtual Imag...

Acceptability, applicability, and cost-utility of artificial-intelligence-powered low-cost portable fundus camera for diabetic retinopathy screening in primary health care settings.

AIMS: To evaluate the acceptability, applicability, and cost-utility of AI-powered portable fundus cameras for diabetic retinopathy (DR) screening in ...

Identification of patients at risk for pancreatic cancer in a 3-year timeframe based on machine learning algorithms.

Early detection of pancreatic cancer (PC) remains challenging largely due to the low population incidence and few known risk factors. However, screeni...

Machine learning of clinical phenotypes facilitates autism screening and identifies novel subgroups with distinct transcriptomic profiles.

Autism spectrum disorder (ASD) presents significant challenges in diagnosis and intervention due to its diverse clinical manifestations and underlying...

Establishing a clinical prediction model for diabetic foot ulcers in type 2 diabetic patients with lower extremity arteriosclerotic occlusion using machine learning.

The burden of diabetic foot ulcers (DFU) is exacerbated in diabetic patients with concomitant arteriosclerotic occlusion disease (ASO) in the lower ex...

HEPOM: Using Graph Neural Networks for the Accelerated Predictions of Hydrolysis Free Energies in Different pH Conditions.

Hydrolysis is a fundamental family of chemical reactions where water facilitates the cleavage of bonds. The process is ubiquitous in biological and ch...

A quantum inspired machine learning approach for multimodal Parkinson's disease screening.

Parkinson's disease, currently the fastest-growing neurodegenerative disorder globally, has seen a 50% increase in cases within just two years. As dis...

An effective PO-RSNN and FZCIS based diabetes prediction and stroke analysis in the metaverse environment.

Chronic disease (CD) like diabetes and stroke impacts global healthcare extensively, and continuous monitoring and early detection are necessary for e...

Clinical implementation of AI-based screening for risk for opioid use disorder in hospitalized adults.

Adults with opioid use disorder (OUD) are at increased risk for opioid-related complications and repeated hospital admissions. Routine screening for p...

Generating evidence to support the role of AI in diabetic eye screening: considerations from the UK National Screening Committee.

Screening for diabetic retinopathy has been shown to reduce the risk of sight loss in people with diabetes, because of early detection and treatment o...

Machine learning models to predict osteoporosis in patients with chronic kidney disease stage 3-5 and end-stage kidney disease.

Chronic kidney disease-mineral bone disorder is a common complication in patients with chronic kidney disease (CKD) and end-stage kidney disease (ESKD...

CausalCervixNet: convolutional neural networks with causal insight (CICNN) in cervical cancer cell classification-leveraging deep learning models for enhanced diagnostic accuracy.

Cervical cancer is a significant global health issue affecting women worldwide, necessitating prompt detection and effective management. According to ...

Pancreatic Cancer Detection and Differentiation from Chronic Pancreatitis: Potential Biomarkers Identified through a High-Throughput Multiplex Proteomic Assay and Machine Learning-Based Analysis.

BACKGROUND: Pancreatic cancer (PC)-screening methods have limited accuracy despite their high clinical demand. Differential diagnosis of chronic pancr...

Integrative Multi-Omics and Routine Blood Analysis Using Deep Learning: Cost-Effective Early Prediction of Chronic Disease Risks.

Chronic noncommunicable diseases (NCDS) are often characterized by gradual onset and slow progression, but the difficulty in early prediction remains ...

Personalized glucose forecasting for people with type 1 diabetes using large language models.

BACKGROUND AND OBJECTIVE: Type 1 Diabetes (T1D) is an autoimmune disease that requires exogenous insulin via Multiple Daily Injections (MDIs) or subcu...