Preventive Care

Vaccine development using artificial intelligence and machine learning: A review.

The COVID-19 pandemic has underscored the critical importance of effective vaccines, yet their development is a challenging and demanding process. It requires identifying antigens that elicit protective immunity, selecting adjuvants that enhance immunogenicity, and designing delivery systems that ensure optimal efficacy. Artificial intelligence (AI) can facilitate this process by using machine lea...

Machine learning-derived peripheral blood transcriptomic biomarkers for early lung cancer diagnosis: Unveiling tumor-immune interaction mechanisms.

Lung cancer continues to be the leading cause of cancer-related mortality worldwide. Early detection and a comprehensive understanding of tumor-immune interactions are crucial for improving patient outcomes. This study aimed to develop a novel biomarker panel utilizing peripheral blood transcriptomics and machine learning algorithms for early lung cancer diagnosis, while simultaneously providing i...

An evaluation of the performance of stopping rules in AI-aided screening for psychological meta-analytical research.

Several AI-aided screening tools have emerged to tackle the ever-expanding body of literature. These tools employ active learning, where algorithms so...

Current status and dilemmas of osteoporosis screening tools: A narrative review.

OBJECTIVE: This review aims to explore the strengths and dilemmas of existing osteoporosis screening tools and suggest possible ways of optimization, ...

Automation of biochemical assays using an open-sourced, inexpensive robotic liquid handler.

High Throughput Screening is crucial in pharmaceutical companies for efficient testing in drug discovery and development. Our Vaccines Analytical Rese...

Colonoscopy polyp classification via enhanced scattering wavelet Convolutional Neural Network.

Among the most common cancers, colorectal cancer (CRC) has a high death rate. The best way to screen for colorectal cancer (CRC) is with a colonoscopy...

FluPMT: Prediction of Predominant Strains of Influenza A Viruses via Multi-Task Learning.

Seasonal influenza vaccines play a crucial role in saving numerous lives annually. However, the constant evolution of the influenza A virus necessitat...

Machine-Learning Application for Predicting Metabolic Dysfunction-Associated Steatotic Liver Disease Using Laboratory and Body Composition Indicators.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a significant global health burden without established curativ...

Enhancing pap smear image classification: integrating transfer learning and attention mechanisms for improved detection of cervical abnormalities.

Cervical cancer remains a major global health challenge, accounting for significant morbidity and mortality among women. Early detection through scree...

COVID-19 vaccinations and their side effects: a scoping systematic review.

The COVID-19 virus has impacted people worldwide, causing significant changes in their lifestyles. Since the emergence of the epidemic, attempts have...

Effectiveness of artificial intelligence assisted colonoscopy on adenoma and polyp miss rate: A meta-analysis of tandem RCTs.

BACKGROUND AND AIMS: One-fourth of colorectal neoplasia is missed at screening colonoscopy, representing the leading cause of interval colorectal canc...

Characterizing the Coefficient of Friction Between a Capsule Robot and the Colon.

OBJECTIVE: A capsule robot (CR) with an onboard active locomotion mechanism, has been developed as a promising alternative to colonoscopy due to its m...

Effect of a novel artificial intelligence-based cecum recognition system on adenoma detection metrics in a screening colonoscopy setting.

BACKGROUND AND AIMS: Cecal intubation in colonoscopy relies on self-reporting. We developed an artificial intelligence-based cecum recognition system ...

Advancements in opportunistic intracranial aneurysm screening: The impact of a deep learning algorithm on radiologists' analysis of T2-weighted cranial MRI.

(1) Background: Unruptured Intracranial Aneurysms (UIAs) are common blood vessel malformations, occurring in up to 3 % of healthy adults. Magnetic Res...

Deep Learning-Based Blood Abnormalities Detection as a Tool for VEXAS Syndrome Screening.

INTRODUCTION: VEXAS is a syndrome described in 2020, caused by mutations of the UBA1 gene, and displaying a large pleomorphic array of clinical and he...

A deep learning approach to prediction of blood group antigens from genomic data.

BACKGROUND: Deep learning methods are revolutionizing natural science. In this study, we aim to apply such techniques to develop blood type prediction...

Development and evaluation of a model for predicting the risk of healthcare-associated infections in patients admitted to intensive care units.

This retrospective study used 10 machine learning algorithms to predict the risk of healthcare-associated infections (HAIs) in patients admitted to in...

Explainable artificial intelligence-driven prostate cancer screening using exosomal multi-marker based dual-gate FET biosensor.

Prostate Imaging Reporting and Data System (PI-RADS) score, a reporting system of prostate MRI cases, has become a standard prostate cancer (PCa) scre...

Application of Machine Learning in a Rodent Malaria Model for Rapid, Accurate, and Consistent Parasite Counts.

Rodent malaria models serve as important preclinical antimalarial and vaccine testing tools. Evaluating treatment outcomes in these models often requi...

Mobil Monitoring Doppler Ultrasound (MoMDUS) study: protocol for a prospective, observational study investigating the use of artificial intelligence and low-cost Doppler ultrasound for the automated quantification of hypertension, pre-eclampsia and fetal growth restriction in rural Guatemala.

INTRODUCTION: Undetected high-risk conditions in pregnancy are a leading cause of perinatal mortality in low-income and middle-income countries. A key...