Primary Care

[Main biological tools applied to newborn screening: Landscape and future perspectives].

Over the past fifty years, neonatal screening has become essential in the public health programs of ...

Integration of NLP2FHIR Representation with Deep Learning Models for EHR Phenotyping: A Pilot Study on Obesity Datasets.

HL7 Fast Healthcare Interoperability Resources (FHIR) is one of the current data standards for enabl...

A comprehensive scoping review of Bayesian networks in healthcare: Past, present and future.

No comprehensive review of Bayesian networks (BNs) in healthcare has been published in the past, mak...

Machine learning applications to neuroimaging for glioma detection and classification: An artificial intelligence augmented systematic review.

Glioma is the most common primary intraparenchymal tumor of the brain and the 5-year survival rate o...

An Artificial-Intelligence-Discovered Functional Ingredient, NRT_N0G5IJ, Derived from , Decreases HbA1c in a Prediabetic Population.

The prevalence of prediabetes is rapidly increasing, and this can lead to an increased risk for indi...

Hopes and Hypes for Artificial Intelligence in Colorectal Cancer Screening.

Eliminating Indefiniteness of Clinical Spectrum for Better Screening COVID-19.

The coronavirus disease 2019 (COVID-19) has swept all over the world. Due to the limited detection f...

A Multiprocessing Scheme for PET Image Pre-Screening, Noise Reduction, Segmentation and Lesion Partitioning.

Accurate segmentation and partitioning of lesions in PET images provide computer-aided procedures an...

Using machine-learning algorithms to identify patients at high risk of upper gastrointestinal lesions for endoscopy.

BACKGROUND AND AIM: Endoscopic screening for early detection of upper gastrointestinal (UGI) lesions...

Drug repurposing for hyperlipidemia associated disorders: An integrative network biology and machine learning approach.

Hyperlipidemia causes diseases like cardiovascular disease, cancer, Type II Diabetes and Alzheimer's...

A combined microfluidic deep learning approach for lung cancer cell high throughput screening toward automatic cancer screening applications.

Lung cancer is a leading cause of cancer death in both men and women worldwide. The high mortality r...

From Reflection to Action: Combining Machine Learning with Expert Knowledge for Nutrition Goal Recommendations.

Self-tracking can help personalize self-management interventions for chronic conditions like type 2 ...

Integrated support vector machine and pharmacophore based virtual screening driven identification of thiophene carboxamide scaffold containing compound as potential PARP1 inhibitor.

Poly (ADP-ribose) polymerase-1 (PARP1) inhibition strategy for cancer treatment is gaining advantage...

Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records.

Early prediction of patient outcomes is important for targeting preventive care. This protocol descr...

AI-based Strategies to Reduce Workload in Breast Cancer Screening with Mammography and Tomosynthesis: A Retrospective Evaluation.

Background The workflow of breast cancer screening programs could be improved given the high workloa...

Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning.

INTRODUCTION: Recent studies have reported that HbA1c and lipid variability is useful for risk strat...

Efficient Automated Disease Diagnosis Using Machine Learning Models.

Recently, many researchers have designed various automated diagnosis models using various supervised...

Evaluation of the VITEK 2 Advanced Expert System performance for predicting resistance mechanisms in Enterobacterales acquired from a hospital-based screening program.

There is limited literature examining the accuracy of the VITEK 2 Advanced Expert System (AES) in ch...

Development and Validation of a Machine Learning Model Using Administrative Health Data to Predict Onset of Type 2 Diabetes.

IMPORTANCE: Systems-level barriers to diabetes care could be improved with population health plannin...

Automated Explainable Multidimensional Deep Learning Platform of Retinal Images for Retinopathy of Prematurity Screening.

IMPORTANCE: A retinopathy of prematurity (ROP) diagnosis currently relies on indirect ophthalmoscopy...

Q-CHAT-NAO: A robotic approach to autism screening in toddlers.

The use of humanoid robots as assistants in therapy processes is not new. Several projects in the pa...