Bioterrorism

Machine learning in paediatric haematological malignancies: a systematic review of prognosis, toxicity and treatment response models.

BACKGROUND: Machine Learning (ML) has demonstrated potential in enhancing care in adult oncology. Ho...

Artificial intelligence for response prediction and personalisation in radiation oncology.

Artificial intelligence (AI) systems may personalise radiotherapy by assessing complex and multiface...

An Integrated Radiopathomics Machine Learning Model to Predict Pathological Response to Preoperative Chemotherapy in Gastric Cancer.

RATIONALE AND OBJECTIVES: Accurately predicting the pathological response to chemotherapy before tre...

Estimating epidemic trajectories of SARS-CoV-2 and influenza A virus based on wastewater monitoring and a novel machine learning algorithm.

The COVID-19 pandemic has altered the circulation of non-SARS-CoV-2 respiratory viruses. In this stu...

Development and validation of a machine learning-based model to assess probability of systemic inflammatory response syndrome in patients with severe multiple traumas.

BACKGROUND: Systemic inflammatory response syndrome (SIRS) is a predictor of serious infectious comp...

Generative commonsense knowledge subgraph retrieval for open-domain dialogue response generation.

Grounding on a commonsense knowledge subgraph can help the model generate more informative and diver...

Optimization of the extraction process of total steroids from (Schwein.) Pat. by artificial neural network (ANN)-response surface methodology and identification of extract constituents.

(Schwein.) Pat has pharmacological effects such as tonifying the spleen, dispelling dampness, and s...

From data to harvest: Leveraging ensemble machine learning for enhanced crop yield predictions across Canada amidst climate change.

Accurate crop yield predictions are crucial for farmers and policymakers. Despite the widespread use...

Editorial: Artificial intelligence solutions for global health and disaster response: challenges and opportunities.

Modeling and Optimization of Ellagic Acid from Chebulae Fructus Using Response Surface Methodology Coupled with Artificial Neural Network.

The dried ripe fruit of Retz. is a common Chinese materia medica, and ellagic acid (EA), isolated f...

Integration of Bioinformatics and Machine Learning to Identify CD8+ T Cell-Related Prognostic Signature to Predict Clinical Outcomes and Treatment Response in Breast Cancer Patients.

UNLABELLED: The incidence of breast cancer (BC) continues to rise steadily, posing a significant bur...

Exploring the response and prediction of phytoplankton to environmental factors in eutrophic marine areas using interpretable machine learning methods.

Coastal marine areas are frequently affected by human activities and face ecological and environment...

Disease Activity and Therapeutic Response to Pegcetacoplan for Geographic Atrophy Identified by Deep Learning-Based Analysis of OCT.

PURPOSE: To quantify morphological changes of the photoreceptors (PRs) and retinal pigment epitheliu...

Robotic flytrap with an ultra-sensitive 'trichome' and fast-response 'lobes'.

Nature abounds with examples of ultra-sensitive perception and agile body transformation for highly ...

Characterization of cardiac resynchronization therapy response through machine learning and personalized models.

INTRODUCTION: The characterization and selection of heart failure (HF) patients for cardiac resynchr...

Robustness of ML-Based Seizure Prediction Using Noisy EEG Data From Limited Channels.

Seizures pose a significant health hazard for over 50 million individuals with epilepsy worldwide, w...

Seismic hazard analysis and financial impact assessment of railway infrastructure in the US West Coast: A machine learning approach.

This research examines the seismic hazard impact on railway infrastructure along the U.S. West Coast...

Pharmacy Student Perceptions of Using AI-Based Interview Software (Big Interview) for Career Preparation.

OBJECTIVE: The goal of this project was to understand the use of artificial intelligence-based inter...

IRnet: Immunotherapy response prediction using pathway knowledge-informed graph neural network.

INTRODUCTION: Immune checkpoint inhibitors (ICIs) are potent and precise therapies for various cance...

New insights on hidradenitis suppurativa phenotypes and treatment response: An exploratory automated analysis of the SUNSHINE and SUNRISE trials.

BACKGROUND: Defining hidradenitis suppurativa (HS) subtypes was previously limited by small sample s...

Optimized phenol degradation and lipid production by Rhodosporidium toruloides using response surface methodology and genetic algorithm-optimized artificial neural network.

Oleaginous yeast can produce lipids while degrading phenol in wastewater treatment. In this study, a...