Primary Care

Outcomes of robot-assisted versus laparoscopic surgery for colorectal cancer in morbidly obese patients: A propensity score-matched analysis of the US Nationwide Inpatient Sample.

BACKGROUND AND AIM: Morbid obesity is associated with poorer postoperative outcomes in colorectal cancer (CRC) patients. We aimed to evaluate short-term outcomes after robotic versus conventional laparoscopic CRC resection in morbidly obese patients.

Combating hypertension beyond genome-wide association studies: Microbiome and artificial intelligence as opportunities for precision medicine.

The single largest contributor to human mortality is cardiovascular disease, the top risk factor for which is hypertension (HTN). The last two decades have placed much emphasis on the identification of genetic factors contributing to HTN. As a result, over 1,500 genetic alleles have been associated with human HTN. Mapping studies using genetic models of HTN have yielded hundreds of blood pressure ...

Deep learning-based measurement of echocardiographic data and its application in the diagnosis of sudden cardiac death.

This study aimed to evaluate the potential of deep learning applied to the measurement of echocardiographic data in patients with sudden cardiac death...

Daring discourse: artificial intelligence in pain medicine, opportunities and challenges.

Artificial intelligence (AI) tools are currently expanding their influence within healthcare. For pain clinics, unfettered introduction of AI may caus...

Machine-learning predictive model of pregnancy-induced hypertension in the first trimester.

In the first trimester of pregnancy, accurately predicting the occurrence of pregnancy-induced hypertension (PIH) is important for both identifying hi...

Exploring the Potential of Chat GPT in Personalized Obesity Treatment.

Obesity has become a serious global health problem. For some patients who cannot be treated with traditional methods, artificial intelligence technolo...

Survey and Evaluation of Hypertension Machine Learning Research.

Background Machine learning (ML) is pervasive in all fields of research, from automating tasks to complex decision-making. However, applications in di...

Deep Learning vs Traditional Models for Predicting Hospital Readmission among Patients with Diabetes.

A hospital readmission risk prediction tool for patients with diabetes based on electronic health record (EHR) data is needed. The optimal modeling ap...

Artificial intelligence innovation in healthcare: Relevance of reporting guidelines for clinical translation from bench to bedside.

Artificial intelligence (AI) and digital innovation are transforming healthcare. Technologies such as machine learning in image analysis, natural lang...

Body composition predicts hypertension using machine learning methods: a cohort study.

We used machine learning methods to investigate if body composition indices predict hypertension. Data from a cohort study was used, and 4663 records ...

Differential diagnosis of secondary hypertension based on deep learning.

Secondary hypertension is associated with higher risks of target organ damage and cardiovascular and cerebrovascular disease events. Early aetiology i...

Interstitial Lung Abnormalities at CT in the Korean National Lung Cancer Screening Program: Prevalence and Deep Learning-based Texture Analysis.

Background Interstitial lung abnormalities (ILAs) are associated with worse clinical outcomes, but ILA with lung cancer screening CT has not been quan...

Utilization of Bioinorganic Nanodrugs and Nanomaterials for the Control of Infectious Diseases Using Deep Learning.

As one of the main causes of morbidity and mortality, viral infections have a major impact on the well-being and economics of every nation in the glob...

Can deep learning on retinal images augment known risk factors for cardiovascular disease prediction in diabetes? A prospective cohort study from the national screening programme in Scotland.

AIMS: This study's objective was to evaluate whether deep learning (DL) on retinal photographs from a diabetic retinopathy screening programme improve...

Updates of precision medicine in type 2 diabetes.

Diabetes mellitus is prevalent worldwide and affects 1 in 10 adults. Despite the successful development of glucose-lowering drugs, such as glucagon-li...

A deep learning nomogram of continuous glucose monitoring data for the risk prediction of diabetic retinopathy in type 2 diabetes.

Continuous glucose monitoring (CGM) data analysis will provide a new perspective to analyze factors related to diabetic retinopathy (DR). However, the...

Artificial intelligence assisted identification of potential tau aggregation inhibitors: ligand- and structure-based virtual screening, in silico ADME, and molecular dynamics study.

Alzheimer's disease (AD) is a severe, growing, multifactorial disorder affecting millions of people worldwide characterized by cognitive decline and n...

Clinically explainable machine learning models for early identification of patients at risk of hospital-acquired urinary tract infection.

BACKGROUND: Machine learning (ML) models for early identification of patients at risk of hospital-acquired urinary tract infection (HA-UTI) may enable...

Excellence in Total Worker Health® and an Interview With Dr Laura Linnan.

The National Institute of Occupational Safety and Health (NIOSH) defines as "policies, programs and practices that integrate protection from work-rel...

Novel Port Placement in Robot-Assisted DIEP Flap Harvest Improves Visibility and Bilateral DIEP Access: Early Controlled Cohort Study.

SUMMARY: To minimize donor-site damage, robot-assisted (RA) deep inferior epigastric perforator (DIEP) flap harvest has been suggested. Current roboti...