Primary Care

Stem Cell-Derived Organoids as a Next-Generation Platform for Drug Toxicity and Efficacy Testing: Toward Replacing Animal Models in Regulatory Science.

Three-dimensional, self-organizing structures derived from stem cells, known as organoids, represent a groundbreaking advancement in preclinical drug development. Organoid-based platforms advance preclinical testing by providing an accurate representation of human tissue architecture and genetics, surpassing traditional two-dimensional cultures and animal models in testing both drug safety and eff...

AI for screening in healthcare: promise and challenges.

Artificial intelligence (AI) is reshaping population screening, yet the translation from laboratory performance to population benefit remains limited. This narrative review describes current uses of AI across major screening pathways. Prospective trials in mammography demonstrate non‑inferior cancer detection with large reductions in radiologist workload. In diabetic retinopathy, the first FDA‑aut...

Clinical assessment of a Near-Infrared spectroscopy device for rapid triage in traumatic brain injury.

BACKGROUND: Traumatic Brain Injury (TBI) poses a significant public health challenge in India, with nearly 2 million cases annually and limited CT ava...

Predicting postpartum glucose intolerance in women with gestational diabetes mellitus in primary care: A machine learning approach using XGBoost and SHAP values.

OBJECTIVE(S): To develop and internally validate an interpretable machine learning model using eXtreme Gradient Boosting (XGBoost) and Shapley Additiv...

Machine learning-based identification of factors associated with spontaneous abortion in patients with Systemic lupus erythematosus (SLE): Insights from the Egyptian College of Rheumatology (ECR)-SLE cohort.

BackgroundSystemic lupus erythematosus (SLE), an autoimmune disease, predominantly affects women and is associated with an increased risk of spontaneo...

A deep learning-based tool for rapid and automated detection of Cryptosporidium oocysts: A new approach for veterinary diagnostics and epizootiological surveys.

Cryptosporidiosis, caused by Cryptosporidium spp., is a significant zoonotic parasitic disease impacting neonatal calves, leading to severe diarrhea, ...

Coronary artery calcium clinical utilization: An update.

Coronary artery disease (CAD) remains a leading cause of mortality and morbidity worldwide. Coronary artery calcification (CAC) is a well-established ...

A clinical dataset on type-2 diabetes including demographic, anthropometric, and biochemical parameters from Bangladesh.

Type-2 diabetes is a major public health concern in Bangladesh, and this dataset provides 1065 curated patient records with demographic, anthropometri...

Predicting cardiovascular diseases using imbalanced data: An XGBoost-based analysis of the 2022 BRFSS dataset.

BACKGROUND: Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, arising from complex interactions among demographic, clini...

Preliminary insights into artificial intelligence guided dosing in hypertension and diabetes: challenges and lessons learnt in a pilot feasibility study.

OBJECTIVE: CURATE.AI is an artificial intelligence platform enabling personalised drug dosing. Aims:1) Determine the feasibility of using CURATE.AI in...

Markers predicting lymphoma development in Sjögren disease: current status and future perspectives.

We aim to present recent advancements in predictive markers for lymphomagenesis in SjD, concisely organize existing knowledge, and identify correspond...

Structure-based virtual screening of ultra-large chemical spaces: Advances and pitfalls.

On-demand chemical spaces consist of molecules that are, a priori, readily synthesizable from sets of commercial building blocks through robust organi...

Machine learning and causal inference applied to the gut metagenome-metabolome axis reveals a link between neonatal jaundice and autism spectrum disorder.

UNLABELLED: Neonatal jaundice (NJ) might increase the risk of autism spectrum disorder (ASD) in children. This study examined whether alterations in t...

Significance and Implications of Prostate Cancer: Critical Overview for Future Directions in Africa.

Prostate cancer places a heavy economic burden on health care in many countries globally. This is no exception in Africa. It is also described as one ...

Predictors of Outcome Clusters in Patients With Unruptured Intracranial Aneurysms Treated With Microsurgery: An Unsupervised Machine Learning Analysis.

BACKGROUND AND OBJECTIVES: Identifying surgical candidates who are prone to poor outcomes is crucial for adapting treatment and ensuring optimal outco...

Diverse intracellular trafficking of insulin analogs by machine learning-based colocalization and diffusion analysis.

Insulin signaling is vital for cellular homeostasis, with dysregulation leading to severe metabolic disorders, particularly diabetes. While insulin an...

Association between the insulin resistance indices and incident type 2 diabetes across different body mass index states: a cohort study and external validation from two East Asian populations.

BACKGROUND: Insulin resistance (IR) indices like the TyG index are predictors of type 2 diabetes (T2DM), but their comparative performance across BMI ...

MRI-to-PET synthesis via deep learning for amyloid-β quantification in Alzheimer's disease.

OBJECTIVES: Amyloid-β (Aβ) PET is crucial for diagnosing and monitoring Alzheimer's disease (AD), but its high cost and radiation exposure limit its u...

How much radiologist time can be saved by implementing AI in screen-reading mammograms?

OBJECTIVE: There is a lack of breast radiologists in Norway and in Europe. Artificial intelligence (AI) offers an alternative to solely human readers ...

Capability of chatbots powered by large language models to support the screening process of scoping reviews: a feasibility study.

OBJECTIVES: The surge in publications increases screening time required to maintain high-quality literature reviews. One of the most time-consuming ph...