Bioterrorism

Response to Letter to the Editor from Partha Pratim Ray: 'Integrating AI in radiology: insights from GPT-generated reports and multimodal LLM performance on European Board of Radiology examinations'.

Deep learning model based on endoscopic images predicting treatment response in locally advanced rectal cancer undergo neoadjuvant chemoradiotherapy: a multicenter study.

PURPOSE: Neoadjuvant chemoradiotherapy has been the standard practice for patients with locally adva...

Response to "Harnessing artificial intelligence in bariatric surgery: correspondence".

The construction of machine learning-based predictive models for high-quality embryo formation in poor ovarian response patients with progestin-primed ovarian stimulation.

OBJECTIVE: To explore the optimal models for predicting the formation of high-quality embryos in Poo...

A novel CAF-cancer cell crosstalk-related gene prognostic index based on machine learning: prognostic significance and prediction of therapeutic response in head and neck squamous cell carcinoma.

BACKGROUND: Cancer-associated fibroblast (CAF)-cancer cell crosstalk (CCCT) plays an important role ...

Response to "Letter to the Editor-Exploring the Unknown: Evaluating ChatGPT's Performance in Uncovering Novel Aspects of Plastic Surgery and Identifying Areas for Future Innovation".

We appreciate Dr. Qi and Dr. Niu for their insightful comments on our study, "Exploring the Unknown:...

Machine learning models to predict systemic inflammatory response syndrome after percutaneous nephrolithotomy.

OBJECTIVE: The objective of this study was to develop and evaluate the performance of machine learni...

A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics.

Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin-stained ...

Beyond code: Consumer response to chatbots.

Chatbots, a type of virtual AI entity designed to emulate human conversation, are gaining prominence...

Modeling and control of COVID-19 disease using deep reinforcement learning method.

The prevalence of epidemics has been studied by researchers in various fields. In the last 2 years, ...

Predicting Therapeutic Response to Hypoglossal Nerve Stimulation Using Deep Learning.

OBJECTIVES: To develop and validate machine learning (ML) and deep learning (DL) models using drug-i...

Infusion of active compound into sliced button mushrooms through vacuum impregnation to improve functionality: Comparing response surface methodology and artificial neural network.

The present study explores the infusion of active compounds (ascorbic acid and calcium lactate) into...

A non-invasive artificial intelligence model for identifying axillary pathological complete response to neoadjuvant chemotherapy in breast cancer: a secondary analysis to multicenter clinical trial.

BACKGROUND: This study aims to develop a stacking model for accurately predicting axillary lymph nod...

Enhanced biosynthesis of coated silver nanoparticles using isolated bacteria from heavy metal soils and their photothermal-based antibacterial activity: integrating Response Surface Methodology (RSM) Hybrid Artificial Neural Network (ANN)-Genetic Algorithm (GA) strategies.

This study explores the biosynthesis of silver nanoparticles (AgNPs) using the Streptomyces tuirus S...

Authors' response: "Development of a machine learning model for prediction of the duration of unassisted spontaneous breathing in patients during prolonged weaning from mechanical ventilation".

Patient-Specific, Mechanistic Models of Tumor Growth Incorporating Artificial Intelligence and Big Data.

Despite the remarkable advances in cancer diagnosis, treatment, and management over the past decade,...

Individual Predictors of Response to A Behavioral Activation-Based Digital Smoking Cessation Intervention: A Machine Learning Approach.

Depression is prevalent among individuals who smoke cigarettes and increases risk for relapse. A pr...

Correlation of limited-early-response status with 12-month CST, BVA, and machine learning-quantified retinal fluid in diabetic macular oedema in routine clinical practice.

BACKGROUND/OBJECTIVES: Anti-VEGF treatment response in DMO has been measured by changes in the centr...

Forecasting of compound ocean-fluvial floods using machine learning.

Flood modelling and forecasting can enhance our understanding of flood mechanisms and facilitate eff...

Response to "Letter to the Editor: The Promise and Pitfalls of AI-Generated Anatomical Images: Evaluating Midjourney for Aesthetic Surgery Applications".

This response letter answers a query regarding our study on the use of the Midjourney app in aesthet...

The use of AI for humanitarian response during conflict: do no digital harm.