Bioterrorism

Multimodal workflows optimally predict response to repetitive transcranial magnetic stimulation in patients with schizophrenia: a multisite machine learning analysis.

The response variability to repetitive transcranial magnetic stimulation (rTMS) challenges the effec...

Diagnosis and Severity Assessment of COPD Using a Novel Fast-Response Capnometer and Interpretable Machine Learning.

INTRODUCTION: Spirometry is the gold standard for COPD diagnosis and severity determination, but is ...

Tailoring Household Disaster Preparedness Interventions to Reduce Health Disparities: Nursing Implications from Machine Learning Importance Features from the 2018-2020 FEMA National Household Survey.

Tailored disaster preparedness interventions may be more effective and equitable, yet little is know...

General Model for Predicting Response of Gas-Sensitive Materials to Target Gas Based on Machine Learning.

Gas sensors play a crucial role in various industries and applications. In recent years, there has b...

Develop and Validate a Nomogram Combining Contrast-Enhanced Spectral Mammography Deep Learning with Clinical-Pathological Features to Predict Neoadjuvant Chemotherapy Response in Patients with ER-Positive/HER2-Negative Breast Cancer.

RATIONALE AND OBJECTIVES: To develop and validate a nomogram that combines contrast-enhanced spectra...

Immune Regulation Patterns in Response to Environmental Pollutant Chromate Exposure-Related Genetic Damage: A Cross-Sectional Study Applying Machine Learning Methods.

Exposure to hexavalent chromium damages genetic materials like DNA and chromosomes, further elevatin...

Postoperative leukocyte counts as a surrogate for surgical stress response in matched robot- and video-assisted thoracoscopic surgery cohorts of patients: A preliminary report.

The objective is to preliminary evaluated postoperative leukocyte counts as a surrogate for the surg...

Predictive value of a stemness-based classifier for prognosis and immunotherapy response of hepatocellular carcinoma based on bioinformatics and machine-learning strategies.

OBJECTIVE: Significant advancements have been made in hepatocellular carcinoma (HCC) therapeutics, s...

Application of ionic liquid ultrasound-assisted extraction (IL-UAE) of lycopene from guava (Psidium guajava L.) by response surface methodology and artificial neural network-genetic algorithm.

Lycopene-rich guava (Psidium guajava L.) exhibits significant economic potential as a functional foo...

Prediction of deep molecular response in chronic myeloid leukemia using supervised machine learning models.

Machine learning-based integration develops a stress response stated T cell (Tstr)-related score for predicting outcomes in clear cell renal cell carcinoma.

BACKGROUND: Establishment of a reliable prognostic model and identification of novel biomarkers are ...

Response accuracy of ChatGPT 3.5 Copilot and Gemini in interpreting biochemical laboratory data a pilot study.

With the release of ChatGPT at the end of 2022, a new era of thinking and technology use has begun. ...

A muti-modal feature fusion method based on deep learning for predicting immunotherapy response.

Immune checkpoint therapy (ICT) has greatly improved the survival of cancer patients in the past few...

DBDNMF: A Dual Branch Deep Neural Matrix Factorization method for drug response prediction.

Anti-cancer response of cell lines to drugs is in urgent need for individualized precision medical d...

Is artificial intelligence true glory? Response to "Generative artificial intelligence in otolaryngology-head and neck surgery editorial: be an actor of the future or follower".

A radiogenomic multimodal and whole-transcriptome sequencing for preoperative prediction of axillary lymph node metastasis and drug therapeutic response in breast cancer: a retrospective, machine learning and international multicohort study.

BACKGROUND: Axillary lymph nodes (ALN) status serves as a crucial prognostic indicator in breast can...

Identifying depression-related topics in smartphone-collected free-response speech recordings using an automatic speech recognition system and a deep learning topic model.

BACKGROUND: Prior research has associated spoken language use with depression, yet studies often inv...

Risk and prosocial behavioural cues elicit human-like response patterns from AI chatbots.

Emotions, long deemed a distinctly human characteristic, guide a repertoire of behaviors, e.g., prom...

Non-invasive prediction for pathologic complete response to neoadjuvant chemoimmunotherapy in lung cancer using CT-based deep learning: a multicenter study.

Neoadjuvant chemoimmunotherapy has revolutionized the therapeutic strategy for non-small cell lung c...

Machine learning-based nomogram to predict poor response to overnight orthokeratology in Chinese myopic children: A multicentre, retrospective study.

PURPOSE: To develop and validate an effective nomogram for predicting poor response to orthokeratolo...

Machine learning framework develops neutrophil extracellular traps model for clinical outcome and immunotherapy response in lung adenocarcinoma.

Neutrophil extracellular traps (NETs) are novel inflammatory cell death in neutrophils. Emerging stu...