Bioterrorism

Deep Learning-Based Stratification of Gastric Cancer Patients from Hematoxylin and Eosin-Stained Whole Slide Images by Predicting Molecular Features for Immunotherapy Response.

Determining the molecular characteristics of cancer patients is crucial for optimal immunotherapy de...

Predicting Neoadjuvant Chemotherapy Response and High-Grade Serous Ovarian Cancer From CT Images in Ovarian Cancer with Multitask Deep Learning: A Multicenter Study.

RATIONALE AND OBJECTIVES: Accurate prediction neoadjuvant chemotherapy (NACT) response in ovarian ca...

Predicting the antigenic evolution of SARS-COV-2 with deep learning.

The relentless evolution of SARS-CoV-2 poses a significant threat to public health, as it adapts to ...

Robot versus human barista: Comparison of volatile compounds and consumers' acceptance, sensory profile, and emotional response of brewed coffee.

The increasing trend of integrating robots into the food industry has sparked debates regarding thei...

Response predictor for pigment reduction after one session of photo-based therapy using convolutional neural network: A proof of concept study.

BACKGROUND: Identifying treatment responders after a single session of photo-based procedure for hyp...

Further remarks on testimonial injustice in medical machine learning: a response to commentaries.

Development of a program to determine optimal settings for robot-assisted rehabilitation of the post-stroke paretic upper extremity: a simulation study.

Robot-assisted therapy can effectively treat upper extremity (UE) paralysis in patients who experien...

A deep learning predictive model for public health concerns and hesitancy toward the COVID-19 vaccines.

Throughout the pandemic era, COVID-19 was one of the remarkable unexpected situations over the past ...

Patient groups in Rheumatoid arthritis identified by deep learning respond differently to biologic or targeted synthetic DMARDs.

Cycling of biologic or targeted synthetic disease modifying antirheumatic drugs (b/tsDMARDs) in rheu...

Deep Learning Model Based on Dual-Modal Ultrasound and Molecular Data for Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer.

RATIONALE AND OBJECTIVES: To carry out radiomics analysis/deep convolutional neural network (CNN) ba...

Response to "Rhinoplasty Consultation with ChatGPT" by Kleebayoon et al.

Decoding the physiological response of plants to stress using deep learning for forecasting crop loss due to abiotic, biotic, and climatic variables.

This paper presents a simple method for detecting both biotic and abiotic stress in plants. Stress l...

Biologically Interpretable Deep Learning To Predict Response to Immunotherapy In Advanced Melanoma Using Mutations and Copy Number Variations.

Only 30-40% of advanced melanoma patients respond effectively to immunotherapy in clinical practice,...

Determination of optimum intensity and duration of exercise based on the immune system response using a machine-learning model.

One of the important concerns in the field of exercise immunology is determining the appropriate int...

Artificial intelligence predicts lung cancer radiotherapy response: A meta-analysis.

BACKGROUND: Artificial intelligence (AI) technology has clustered patients based on clinical feature...

Re: Vogl et al.: Predicting topographic disease progression and treatment response of pegcetacoplan in geographic atrophy quantified by deep learning (Ophthalmol Retina. 2023;7:4-13).

Deep learning on independent spatial EEG activity patterns delineates time windows relevant for response inhibition.

Inhibitory control processes are an important aspect of executive functions and goal-directed behavi...

Animal disease surveillance: How to represent textual data for classifying epidemiological information.

The value of informal sources in increasing the timeliness of disease outbreak detection and providi...

A fully automated micro‑CT deep learning approach for precision preclinical investigation of lung fibrosis progression and response to therapy.

Micro-computed tomography (µCT)-based imaging plays a key role in monitoring disease progression and...

Can ChatGPT Accurately Answer a PICOT Question? Assessing AI Response to a Clinical Question.

BACKGROUND: ChatGPT, an artificial intelligence (AI) text generator trained to predict correct words...

Assessment of stress response due to C-Mac D-blade guided videolaryngoscopic endotracheal intubation and docking of da Vinci surgical robot using perfusion index in patients undergoing transoral robotic oncosurgery.

Clinical utility of perfusion index (PI) has entered a new realm as a non-invasive, quantitative ind...