Preventive Care

Using Large Language Models for sentiment analysis of health-related social media data: empirical evaluation and practical tips.

Health-related social media data generated by patients and the public provide valuable insights into patient experiences and opinions toward health issues such as vaccination and medical treatments. Using Natural Language Processing (NLP) methods to analyze such data, however, often requires high-quality annotations that are difficult to obtain. The recent emergence of Large Language Models (LLMs)...

Estimating classification consistency of machine learning models for screening measures.

This article illustrates novel quantitative methods to estimate classification consistency in machine learning models used for screening measures. Screening measures are used in psychology and medicine to classify individuals into diagnostic classifications. In addition to achieving high accuracy, it is ideal for the screening process to have high classification consistency, which means that respo...

Deep-learning model for prenatal congenital heart disease screening generalizes to community setting and outperforms clinical detection.

OBJECTIVES: Despite nearly universal prenatal ultrasound screening programs, congenital heart defects (CHD) are still missed, which may result in seve...

Peri-lesion regions in differentiating suspicious breast calcification-only lesions specifically on contrast enhanced mammography.

PURPOSE: The explore the added value of peri-calcification regions on contrast-enhanced mammography (CEM) in the differential diagnosis of breast lesi...

Breast Mass Detection and Classification Using Machine Learning Approaches on Two-Dimensional Mammogram: A Review.

Breast cancer is a leading cause of mortality among women, both in India and globally. The prevalence of breast masses is notably common in women aged...

Artificial intelligence in diabetic retinopathy screening: from idea to a medical device in clinical practice.

With the growing significance of artificial intelligence in healthcare, new perspectives are emerging in primary care. Diabetic retinopathy, a microva...

Computer-aided Detection and Diagnosis of Cancer Regions in Mammogram Images Using Resource-Efficient CNN Architecture.

AIM: The automatic computer-assisted mammogram classification system is important for women patients to detect and diagnose the cancer regions. In thi...

Identification and Prioritization of Health Indexes in Nomadic Tribespeople by Fuzzy Delphi Method: An Ecological Study.

The migratory lifestyle of nomadic communities, combined with the lack of a suitable health-related organizational structure, has made it difficult to...

The Growing Impact of Natural Language Processing in Healthcare and Public Health.

Natural Language Processing (NLP) is a subset of Artificial Intelligence, specifically focused on understanding and generating human language. NLP tec...

[Application and evaluation of artificial intelligence TPS-assisted cytologic screening system in urine exfoliative cytology].

To explore the application of manual screening collaborated with the Artificial Intelligence TPS-Assisted Cytologic Screening System in urinary exfol...

[Advancements in virtual screening techniques for study of enzyme inhibitor compounds].

Enzymes are closely associated with the onset and progression of numerous diseases, making enzymes a primary target in innovative drug development. Ho...

[Experimental study of APB-DOCK8 transgenic tomato vaccine for caries prevention].

PURPOSE: To observe the anti-caries effect of transgenic tomato anti-caries vaccine after immunization with SD rats by gavage and to explore its immun...

Mammography Breast Cancer Screening Triage Using Deep Learning: A UK Retrospective Study.

Background Breast screening enables early detection of cancers; however, most women have normal mammograms, resulting in repetitive and resource-inten...

Efficacy of Pulse Methylprednisolone in Treatment of Acute Respiratory Distress Syndrome due to Malaria: A Randomized Controlled Clinical Trial.

: To study the efficacy of pulse methylprednisolone (MPS) therapy in patients with malaria-associated acute respiratory distress syndrome (ARDS). : Th...

Comparison of the Diagnostic Accuracy of Mammogram-based Deep Learning and Traditional Breast Cancer Risk Models in Patients Who Underwent Supplemental Screening with MRI.

Background Access to supplemental screening breast MRI is determined using traditional risk models, which are limited by modest predictive accuracy. P...

Humoral Response After Two Doses of COVISHIELD Vaccine in Patients Undergoing Maintenance Hemodialysis.

OBJECTIVES: Maintenance hemodialysis (MHD) patients are at increased risk of contracting coronavirus disease 2019 (COVID-19). Vaccine against COVID-19...

SEINN: A deep learning algorithm for the stochastic epidemic model.

Stochastic modeling predicts various outcomes from stochasticity in the data, parameters and dynamical system. Stochastic models are deemed more appro...

Reinforcement learning relieves the vaccination dilemma.

The main goal of this paper is to study how a decision-making rule for vaccination can affect epidemic spreading by exploiting the Bush-Mosteller (BM)...

3-LbNets: Tri-Labeling Deep Convolutional Neural Network for the Automated Screening of Glaucoma, Glaucoma Suspect, and No Glaucoma in Fundus Images.

Early detection of glaucoma, a widespread visual disease, can prevent vision loss. Unfortunately, ophthalmologists are scarce and clinical diagnosis r...

A Deep Learning Framework for Image-Based Screening of Kawasaki Disease.

Kawasaki disease (KD) is a leading cause of acquired heart disease in children and is characterized by the presence of a combination of five clinical ...