Bioterrorism

Identifying predictive features in drug response using machine learning: opportunities and challenges.

This article reviews several techniques from machine learning that can be used to study the problem ...

Comparison of response surface methodology and artificial neural network approach towards efficient ultrasound-assisted biodiesel production from muskmelon oil.

The present study is to evaluate and compare the prediction and simulating efficiencies of response ...

Artificial Intelligence Algorithm Predicts Response to Immune Checkpoint Inhibitors.

PURPOSE: Cancer treatment has been revolutionized by immune checkpoint inhibitors (ICI). However, a ...

Harnessing public sentiment discourse for early drought detection and water crisis response for strategic water management and resilient policy planning.

The extensive and gradual onset of drought prompts critical examination of the alterations and engag...

Factors Shaping Healthcare Professionals' Perceptions of AI in Saudi Arabia: A Cross-Sectional Study.

The successful adoption of artificial intelligence (AI) in healthcare relies on healthcare professio...

A Computational Framework for Tailored Preventive Care Recommendations Using Electronic Health Records.

Most healthcare systems worldwide are designed to be reactive. According to the U.S. Centers for Dis...

Response to "Determining Whether the Glymphatic System is Truly Impaired in Pediatric Patients With Refractory Epilepsy Requires Appropriately Designed Studies".

Polarization of dryland vegetation response to spring flood.

Dryland vegetation plays a pivotal role in the global ecosystem and is extraordinarily sensitive to ...

Structure and function of Vitis vinifera Arabidopsis Response Regulator 1 (VvARR1) protein provide insights into the regulatory mechanism of grape fruit shape through gibberellin-cytokinin crosstalk.

Grape fruit shape is a crucial agricultural trait that significantly impacts the commercial value of...

Applying exposure-response analysis to enhance Mycophenolate Mofetil dosing precision in pediatric patients with immune-mediated renal diseases by machine learning models.

BACKGROUND: Mycophenolate mofetil (MMF), a cornerstone immunosuppressant for lupus nephritis, is inc...

Non-invasive CT based multiregional radiomics for predicting pathologic complete response to preoperative neoadjuvant chemoimmunotherapy in non-small cell lung cancer.

PURPOSE: This study aims to develop and validate a multiregional radiomics model to predict patholog...

SARS-CoV-2: lessons in virus mutation prediction and pandemic preparedness.

The COVID-19 pandemic has prompted an unprecedented global response. In particular, extraordinary ef...

Response to Lee and Tung "Critical considerations remain for utilizing artificial intelligence chatbot to translate dermatopathology reports".

Droplet microfluidics integrated with machine learning reveals how adipose-derived stem cells modulate endocrine response and tumor heterogeneity in ER breast cancer.

Approximately 70% of breast cancer (BC) diagnoses are estrogen receptor positive (ER) with ∼40% of E...

Application of Fourier transform infrared (FTIR) spectroscopy in liquid biopsy to predict the response to the first-line immunotherapy in non-small-cell lung cancer (NSCLC) patients.

The direction of anticancer therapies has changed in recent years, including the increasing use of i...

IPEM topical report: results of a 2024 UK survey of artificial intelligence in medical physics and clinical engineering.

Medical physics and clinical engineering (MPCE) professionals have a critical role in the safe and e...

Data-driven multi-hazard susceptibility and community perceptions assessment using a mixed-methods approach.

Assessing multi-hazard susceptibility and understanding community insights are important for effecti...

Machine learning prediction of pathological complete response to neoadjuvant chemotherapy with peritumoral breast tumor ultrasound radiomics: compare with intratumoral radiomics and clinicopathologic predictors.

PURPOSE: Noninvasive, accurate and novel approaches to predict patients who will achieve pathologica...

Radiomics-based machine learning in prediction of response to neoadjuvant chemotherapy in osteosarcoma: A systematic review and meta-analysis.

BACKGROUND AND AIMS: Osteosarcoma (OS) is the most common primary bone malignancy, and neoadjuvant c...

Identifying smart technology and artificial intelligence solutions for human factors and ergonomic challenges in all-hazard response: A survey study.

Emergency responders face significant human factors and ergonomic (HF/E) challenges related to physi...

Improved Machine Learning Predictions of EC50s Using Uncertainty Estimation from Dose-Response Data.

In early-stage drug design, machine learning models often rely on compressed representations of data...