Bioterrorism

Revolutionizing breast cancer immunotherapy by integrating AI and nanotechnology approaches: review of current applications and future directions.

Breast cancer (BC) is still the most diagnosed cancer for females with an increased focus on immunot...

A machine learning model for predicting anatomical response to Anti-VEGF therapy in diabetic macular edema.

PURPOSE: To develop a machine learning model to predict anatomical response to anti-VEGF therapy in ...

Machine Learning-Based Prediction of Post-Operative Systemic Inflammatory Response Syndrome Following Pediatric Percutaneous Nephrolithotripsy.

OBJECTIVE: This study aimed to develop and validate a machine learning-based model for predicting sy...

Response to "Comment on 'Differential Diagnosis of Urinary Cancers by Surface-Enhanced Raman Spectroscopy and Machine Learning'".

Hotspots and Trends in Research on Early Warning of Infectious Diseases: A Bibliometric Analysis Using CiteSpace.

Emerging and re-emerging infectious diseases (EIDs and Re-EIDs) cause significant economic crises a...

Empowering Pharmacists in Type 2 Diabetes Care: Opportunities for Prevention, Counseling, and Therapeutic Optimization.

Diabetes is a growing chronic disease with complications that impose a significant burden on healthc...

Serum-Based Assessment of Alopecia Areata Response to Treatment Using ATR-FTIR Spectroscopy.

: Serum diagnostic tests for alopecia areata may be used to monitor response to treatment, aiding in...

Blockchain based electronic educational document management with role-based access control using machine learning model.

The emergence of digital technology has led to a significant increase in the importance of education...

Hyperspectral imaging to characterize the vegetative tissue biochemical changes in response to water deficit conditions in sorghum ().

Hyperspectral imaging has been used to determine plant stress status. However, the biological interp...

Development of CSOARG: a single-cell and multi-omics-based machine learning model for ovarian cancer prognosis and drug response prediction.

OBJECTIVE: Ovarian cancer is the most deadly gynaecological malignancy. This study aims to generate ...

Ecofriendly Extraction of Polyphenols from Leaves Coupled with Response Surface Methodology and Artificial Neural Network-Genetic Algorithm.

This study aimed to optimize a novel deep eutectic solvents (DESs)-assisted extraction process for p...

Predicting rTMS treatment response in depression: use of machine learning models to identify the roles of metabolic and clinical factors.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for depres...

A novel deep learning framework with artificial protozoa optimization-based adaptive environmental response for wind power prediction.

Accurate very short-term wind power forecasting is critical for the reliable integration of renewabl...

Comparative Evaluation of ChatGPT and ChatGLM Performance in Response to Common Queries on Pediatric Atopic Dermatitis.

BACKGROUND: Atopic dermatitis (AD) is a prevalent chronic and recurrent skin condition in children. ...

Multiband EEG signatures decoded using machine learning for predicting rTMS treatment response in MDD.

BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is a promising treatment for major d...

Depression is associated with treatment response trajectories in adults with Prolonged Grief Disorder: A machine learning analysis.

BACKGROUND: Although evidence-based Prolonged Grief Disorder treatments (PGDT) exist, pretreatment c...

Leveraging pre-vaccination antibody titres across multiple influenza H3N2 variants to forecast the post-vaccination response.

BACKGROUND: Despite decades of research on the influenza virus, we still lack a predictive understan...

Predicting treatment response in individuals with major depressive disorder using structural MRI-based similarity features.

BACKGROUND: Major Depressive Disorder (MDD) is a prevalent mental health condition with significant ...

Burn disasters in North Carolina: An Analysis of Four Major Incidents with a Look to the Future.

This paper examines the medical response to four significant burn disasters in the North Carolina: t...

Machine Learning Analysis of Whole-Blood Transcriptomics Data in Rheumatoid Arthritis Patients Treated with Adalimumab Identifies Predictive Biomarkers of Response.

OBJECTIVES: Tumor necrosis factor inhibitors (TNFi) have significantly improved rheumatoid arthritis...

Insights Into the Future: Assessing Medical Students' Artificial Intelligence Readiness - A Cross-Sectional Study at Kerman University of Medical Sciences (2022).

BACKGROUND: Artificial intelligence (AI) has recently advanced in medicine globally, transforming he...