Primary Care

Deep Learning Using Chest Radiographs to Identify High-Risk Smokers for Lung Cancer Screening Computed Tomography: Development and Validation of a Prediction Model.

BACKGROUND: Lung cancer screening with chest computed tomography (CT) reduces lung cancer death. Centers for Medicare & Medicaid Services (CMS) eligibility criteria for lung cancer screening with CT require detailed smoking information and miss many incident lung cancers. An automated deep-learning approach based on chest radiograph images may identify more smokers at high risk for lung cancer who...

Use of Steroid Profiling Combined With Machine Learning for Identification and Subtype Classification in Primary Aldosteronism.

IMPORTANCE: Most patients with primary aldosteronism, a major cause of secondary hypertension, are not identified or appropriately treated because of difficulties in diagnosis and subtype classification. Applications of artificial intelligence combined with mass spectrometry-based steroid profiling could address this problem.

Computational Radiology in Breast Cancer Screening and Diagnosis Using Artificial Intelligence.

Breast cancer screening has been shown to significantly reduce mortality in women. The increased utilization of screening examinations has led to grow...

Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast during ramadan (The PROFAST - IT Ramadan study).

OBJECTIVE: To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemi...

Case of slowly progressive type 1 diabetes mellitus with drastically reduced insulin secretory capacity after immune checkpoint inhibitor treatment for advanced renal cell carcinoma.

We encountered a 55-year-old Japanese man with advanced renal cell carcinoma and slowly progressive type 1 diabetes mellitus (SPT1DM), whose insulin s...

ANTIPROLIFERATIVE PROPERTIES OF ETHANOLIC AND AQUEOUS GRAVIOLA LEAF EXTRACTS ON TONGUE SQUAMOUS CELL CARCINOMA CELL LINE-25.

BACKGROUND: commonly known as Graviola, soursop or guanabana, is an evergreen tree native to the tropics with a long history of use in ethnomedicine ...

Impact of obesity on surgical and oncologic outcomes in patients with endometrial cancer treated with a robotic approach.

AIM: The surgical treatment of endometrial cancer (EC) can be more complicated in obese patients. Robotic surgery could simplify the surgical approach...

Improved Scaffold Hopping in Ligand-Based Virtual Screening Using Neural Representation Learning.

Deep learning has demonstrated significant potential in advancing state of the art in many problem domains, especially those benefiting from automated...

Applications of Artificial Intelligence in Musculoskeletal Imaging: From the Request to the Report.

Artificial intelligence (AI) will transform every step in the imaging value chain, including interpretive and noninterpretive components. Radiologists...

Humanoid robot-assisted interventions among children with diabetes: A systematic scoping review.

BACKGROUND: Although the humanoid robot is highly engaging for children, whether humanoid robot-assisted interventions could help in diabetes manageme...

Machine Learning Models to Predict Childhood and Adolescent Obesity: A Review.

The prevalence of childhood and adolescence overweight an obesity is raising at an alarming rate in many countries. This poses a serious threat to the...

Point-of-Care Quantification of Serum Alpha-Fetoprotein for Screening Birth Defects in Resource-Limited Settings: Proof-of-Concept Study.

BACKGROUND: Maternal serum alpha-fetoprotein (MSAFP) concentration typically increases during pregnancy and is routinely measured during the second tr...

Screening of Therapeutic Agents for COVID-19 Using Machine Learning and Ensemble Docking Studies.

The current pandemic demands a search for therapeutic agents against the novel coronavirus SARS-CoV-2. Here, we present an efficient computational str...

Development and Cross-Validation of a Nomogram for Chronic Kidney Disease Following Robot-Assisted Radical Cystectomy.

We sought to identify the factors associated with deterioration of renal functions after robot-assisted radical cystectomy, and to develop a nomogram...

Natural Language Processing for Rapid Response to Emergent Diseases: Case Study of Calcium Channel Blockers and Hypertension in the COVID-19 Pandemic.

BACKGROUND: A novel disease poses special challenges for informatics solutions. Biomedical informatics relies for the most part on structured data, wh...

Machine Learning based histology phenotyping to investigate the epidemiologic and genetic basis of adipocyte morphology and cardiometabolic traits.

Genetic studies have recently highlighted the importance of fat distribution, as well as overall adiposity, in the pathogenesis of obesity-associated ...

Diagnosis of diabetes in pregnant woman using a Chaotic-Jaya hybridized extreme learning machine model.

As stated by World Health Organization (WHO) report, 246 million individuals have suffered with diabetes disease over worldwide and it is anticipated ...

A Novel Approach for Continuous Health Status Monitoring and Automatic Detection of Infection Incidences in People With Type 1 Diabetes Using Machine Learning Algorithms (Part 2): A Personalized Digital Infectious Disease Detection Mechanism.

BACKGROUND: Semisupervised and unsupervised anomaly detection methods have been widely used in various applications to detect anomalous objects from a...

Development and clinical application of deep learning model for lung nodules screening on CT images.

Lung cancer screening based on low-dose CT (LDCT) has now been widely applied because of its effectiveness and ease of performance. Radiologists who e...

Predictive modeling by deep learning, virtual screening and molecular dynamics study of natural compounds against SARS-CoV-2 main protease.

The whole world is facing a great challenging time due to Coronavirus disease (COVID-19) caused by SARS-CoV-2. Globally, more than 14.6 M people have ...