Surveillance

Hepatitis C Virus Saint Petersburg Variant Detection With Machine Learning Methods.

Hepatitis C virus infection is a significant global health concern, affecting millions worldwide. Al...

Ovarian-adnexal reporting and data system MRI scoring: diagnostic accuracy, interobserver agreement, and applicability to machine learning.

OBJECTIVES: To evaluate the interobserver agreement and diagnostic accuracy of ovarian-adnexal repor...

A causal machine-learning framework for studying policy impact on air pollution: a case study in COVID-19 lockdowns.

When studying the impact of policy interventions or natural experiments on air pollution, such as ne...

Cholera Outbreak in Nigeria: History, Review of Socioeconomic and Meteorological Drivers, Diagnostic Challenges, and Artificial Intelligence Integration.

Cholera continues to pose a significant public health challenge in Nigeria, driven by socioeconomic ...

An exploration of current and future vector-borne disease threats and opportunities for change.

Vector-borne diseases, including dengue, threaten the health and livelihoods of over 80% of the worl...

Anomaly recognition in surveillance based on feature optimizer using deep learning.

Surveillance systems are integral to ensuring public safety by detecting unusual incidents, yet exis...

Automatic large-scale political bias detection of news outlets.

Political bias is an inescapable characteristic in news and media reporting, and understanding what ...

Ensemble learning guided survival prediction and chemotherapy benefit analysis in high-grade chondrosarcoma: A study based on the surveillance, epidemiology, and end results (SEER) database.

The chemotherapy benefit for high-grade chondrosarcoma remains controversial. Ensemble learning has...

Retraction: Machine learning-based anomaly detection and prediction in commercial aircraft using autonomous surveillance data.

Leveraging artificial intelligence to promote COVID-19 appropriate behaviour in a healthcare institution from north India: A feasibility study.

Background & Objectives Non-pharmacological interventions (NPI) were crucial in curbing the initial ...

[Risk prediction of Reduning Injection batches by near-infrared spectroscopy combined with multiple machine learning algorithms].

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial pr...

[Interpretation of the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis based on regression or machine learning methods (TRIPOD+AI)].

Machine learning-based individualized survival prediction model for prognosis in osteosarcoma: Data from the SEER database.

Patient outcomes of osteosarcoma vary because of tumor heterogeneity and treatment strategies. This ...

[Progress in application of machine learning in epidemiology].

Population based health data collection and analysis are important in epidemiological research. In r...

New horizons in prediction modelling using machine learning in older people's healthcare research.

Machine learning (ML) and prediction modelling have become increasingly influential in healthcare, p...

Reporting standards to support cost-effectiveness evaluations of AI-driven health care.

Deep Learning-based Unsupervised Domain Adaptation via a Unified Model for Prostate Lesion Detection Using Multisite Biparametric MRI Datasets.

Purpose To determine whether the unsupervised domain adaptation (UDA) method with generated images i...

Improving the Quality of Unstructured Cancer Data Using Large Language Models: A German Oncological Case Study.

With cancer being a leading cause of death globally, epidemiological and clinical cancer registratio...

Towards a Reporting Guideline for Studies on Information Extraction from Clinical Texts.

BACKGROUND: The rapid technical progress in the domain of clinical Natural Language Processing and i...

Ontologies related to livestock for the Global Burden of Animal Diseases programme: a review.

The Global Burden of Animal Diseases (GBADs) programme aims to assess the impact of animal health on...

Using AI to Identify Unremarkable Chest Radiographs for Automatic Reporting.

Background Radiology practices have a high volume of unremarkable chest radiographs and artificial i...