Primary Care

Radiomics side experiments and DAFIT approach in identifying pulmonary hypertension using Cardiac MRI derived radiomics based machine learning models.

Side experiments are performed on radiomics models to improve their reproducibility. We measure the ...

Robotic Applications in Orthodontics: Changing the Face of Contemporary Clinical Care.

The last decade (2010-2021) has witnessed the evolution of robotic applications in orthodontics. Thi...

Optimizing Robotic Hysterectomy for the Patient Who Is Morbidly Obese with a Surgical Safety Pathway.

STUDY OBJECTIVE: Obesity is a growing worldwide epidemic, and patients classified as obese undergoin...

Deep-learning models for the detection and incidence prediction of chronic kidney disease and type 2 diabetes from retinal fundus images.

Regular screening for the early detection of common chronic diseases might benefit from the use of d...

ECG for Screening Cardiac Abnormalities: The Premise and Promise of Machine Learning.

Future of biomarker evaluation in the realm of artificial intelligence algorithms: application in improved therapeutic stratification of patients with breast and prostate cancer.

Clinical workflows in oncology depend on predictive and prognostic biomarkers. However, the growing ...

Novel deep learning-based transcriptome data analysis for drug-drug interaction prediction with an application in diabetes.

BACKGROUND: Drug-drug interaction (DDI) is a serious public health issue. The L1000 database of the ...

Wide range of applications for machine-learning prediction models in orthopedic surgical outcome: a systematic review.

Background and purpose - Advancements in software and hardware have enabled the rise of clinical pre...

Weighing features of lung and heart regions for thoracic disease classification.

BACKGROUND: Chest X-rays are the most commonly available and affordable radiological examination for...

Diagnosis of Chronic Kidney Disease Using Effective Classification Algorithms and Recursive Feature Elimination Techniques.

Chronic kidney disease (CKD) is among the top 20 causes of death worldwide and affects approximately...

A novel stacking technique for prediction of diabetes.

BACKGROUND: Machine Learning (ML) represents a rapidly growing technology that supplies the most eff...

Deep Learning on Chest X-ray Images to Detect and Evaluate Pneumonia Cases at the Era of COVID-19.

Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu....

Understanding providers' attitudes and key concerns toward incorporating CVD risk prediction into clinical practice: a qualitative study.

BACKGROUND: Although risk prediction has become an integral part of clinical practice guidelines for...

Computational representations of protein-ligand interfaces for structure-based virtual screening.

: Structure-based virtual screening (SBVS) is an essential strategy for hit identification. SBVS pri...

Can we screen for pancreatic cancer? Identifying a sub-population of patients at high risk of subsequent diagnosis using machine learning techniques applied to primary care data.

BACKGROUND: Pancreatic cancer (PC) represents a substantial public health burden. Pancreatic cancer ...

FTIR spectroscopy with machine learning: A new approach to animal DNA polymorphism screening.

Technological advances in recent decades, especially in molecular genetics, have enabled the detecti...

Machine Learning Boosted Docking (HASTEN): An Open-source Tool To Accelerate Structure-based Virtual Screening Campaigns.

The software macHine leArning booSTEd dockiNg (HASTEN) was developed to accelerate structure-based v...

Predictive analysis of the number of human brucellosis cases in Xinjiang, China.

Brucellosis is one of the major public health problems in China, and human brucellosis represents a ...

Functional link convolutional neural network for the classification of diabetes mellitus.

Diabetes is a faction of metabolic ailments distinguished by hyperglycemia which is the consequence ...

Power of big data to improve patient care in gastroenterology.

Big data is defined as being large, varied or frequently updated, and usually generated from real-wo...

Multiple machine learning models combined with virtual screening and molecular docking to identify selective human ALDH1A1 inhibitors.

Aldehyde dehydrogenases (ALDHs) are the enzymes of oxidoreductase family that are responsible for th...