Primary Care

Artificial intelligence-based multi-omics analysis fuels cancer precision medicine.

With biotechnological advancements, innovative omics technologies are constantly emerging that have enabled researchers to access multi-layer information from the genome, epigenome, transcriptome, proteome, metabolome, and more. A wealth of omics technologies, including bulk and single-cell omics approaches, have empowered to characterize different molecular layers at unprecedented scale and resol...

The potential role of machine learning in modelling advanced chronic liver disease.

The use of artificial intelligence is rapidly increasing in medicine to support clinical decision making mostly through diagnostic and prediction models. Such models derive from huge databases (big data) including a large variety of health-related individual patient data (input) and the corresponding diagnosis and/or outcome (labels). Various types of algorithms (e.g. neural networks) based on pow...

Deep Learning-Based ADHD and ADHD-RISK Classification Technology through the Recognition of Children's Abnormal Behaviors during the Robot-Led ADHD Screening Game.

Although attention deficit hyperactivity disorder (ADHD) in children is rising worldwide, fewer studies have focused on screening than on the treatmen...

Personalized Blood Glucose Prediction for Type 1 Diabetes Using Evidential Deep Learning and Meta-Learning.

The availability of large amounts of data from continuous glucose monitoring (CGM), together with the latest advances in deep learning techniques, hav...

Deep-Learning-Based ADHD Classification Using Children's Skeleton Data Acquired through the ADHD Screening Game.

The identification of attention deficit hyperactivity disorder (ADHD) in children, which is increasing every year worldwide, is very important for ear...

Time for Using Machine Learning for Dose Guidance in Titration of People With Type 2 Diabetes? A Systematic Review of Basal Insulin Dose Guidance.

BACKGROUND: Real-world studies of people with type 2 diabetes (T2D) have shown insufficient dose adjustment during basal insulin titration in clinical...

Prediction of Coronary Artery Calcium Using Deep Learning of Echocardiograms.

BACKGROUND: Coronary artery calcification (CAC), often assessed by computed tomography (CT), is a powerful marker of coronary artery disease that can ...

Behaviour recommendations with a deep learning model and genetic algorithm for health debt characterisation.

Human behaviour is a dense longitudinal multi-featured measure that directly impacts the health of individuals in the short and long terms. Therefore,...

Forecasting blood demand for different blood groups in Shiraz using auto regressive integrated moving average (ARIMA) and artificial neural network (ANN) and a hybrid approaches.

Providing fresh blood to keep people in need of blood alive, has always been a main issues of health systems. Right policy-making in this area require...

Automatic Assessment of Functional Movement Screening Exercises with Deep Learning Architectures.

(1) Background: The success of physiotherapy depends on the regular and correct unsupervised performance of movement exercises. A system that automati...

Personal Precise Force Field for Intrinsically Disordered and Ordered Proteins Based on Deep Learning.

Intrinsically disordered proteins (IDPs) are proteins without a fixed three-dimensional (3D) structure under physiological conditions and are associat...

Diagnostic test accuracy of artificial intelligence-based imaging for lung cancer screening: A systematic review and meta-analysis.

BACKGROUND: Lung cancer is the principal cause of cancer-related deaths worldwide. Early detection of lung cancer with screening is indispensable to r...

Personalized dental medicine, artificial intelligence, and their relevance for dentomaxillofacial imaging.

Personalized medicine refers to the tailoring of diagnostics and therapeutics to individuals based on one's biological, social, and behavioral charact...

Development of an Intelligent System for the Monitoring and Diagnosis of the Well-Being.

Today, society is more aware of their well-being and health, making wearable devices a new and affordable way to track them continuously. Smartwatches...

Automation: A revolutionary vision of artificial intelligence in theranostics.

The last two decades have witnessed an extraordinary evolution of automation and artificial intelligence (AI), which has become an integral part of ou...

Classification of Mental Stress from Wearable Physiological Sensors Using Image-Encoding-Based Deep Neural Network.

The human body is designed to experience stress and react to it, and experiencing challenges causes our body to produce physical and mental responses ...

Pragmatic screening for heart failure in the general population using an electrocardiogram-based neural network.

AIMS: We aim to develop a pragmatic screening tool for heart failure at the general population level.

Improving colorectal cancer screening - consumer-centred technological interventions to enhance engagement and participation amongst diverse cohorts.

The current "Gold Standard" colorectal cancer (CRC) screening approach of faecal occult blood test (FOBT) with follow-up colonoscopy has been shown to...

Applications of Artificial Intelligence to Obesity Research: Scoping Review of Methodologies.

BACKGROUND: Obesity is a leading cause of preventable death worldwide. Artificial intelligence (AI), characterized by machine learning (ML) and deep l...

Machine Learning-Based Models with High Accuracy and Broad Applicability Domains for Screening PMT/vPvM Substances.

Persistent, mobile, and toxic (PMT) substances and very persistent and very mobile (vPvM) substances can transport over long distances from various so...