Bioterrorism

Machine learning in the prediction of immunotherapy response and prognosis of melanoma: a systematic review and meta-analysis.

BACKGROUND: The emergence of immunotherapy has changed the treatment modality for melanoma and prolo...

Emergency Response Person Localization and Vital Sign Estimation Using a Semi-Autonomous Robot Mounted SFCW Radar.

The large number and scale of natural and man-made disasters have led to an urgent demand for techno...

Evaluation of the Current Status of Artificial Intelligence for Endourology Patient Education: A Blind Comparison of ChatGPT and Google Bard Against Traditional Information Resources.

Artificial intelligence (AI) platforms such as ChatGPT and Bard are increasingly utilized to answer...

Effectiveness of artificial intelligence vs. human coaching in diabetes prevention: a study protocol for a randomized controlled trial.

BACKGROUND: Prediabetes is a highly prevalent condition that heralds an increased risk of progressio...

Evaluating the predictive value of angiogenesis-related genes for prognosis and immunotherapy response in prostate adenocarcinoma using machine learning and experimental approaches.

BACKGROUND: Angiogenesis, the process of forming new blood vessels from pre-existing ones, plays a c...

Prediction of treatment response after stereotactic radiosurgery of brain metastasis using deep learning and radiomics on longitudinal MRI data.

We developed artificial intelligence models to predict the brain metastasis (BM) treatment response ...

Machine-learning developed an iron, copper, and sulfur-metabolism associated signature predicts lung adenocarcinoma prognosis and therapy response.

BACKGROUND: Previous studies have largely neglected the role of sulfur metabolism in LUAD, and no st...

A prospective cohort-based artificial intelligence evaluation system for the protective efficacy and immune response of SARS-CoV-2 inactivated vaccines.

BACKGROUND: Novel coronaviruses constitute a significant health threat, prompting the adoption of va...

What do you think caused your ALS? An analysis of the CDC national amyotrophic lateral sclerosis patient registry qualitative risk factor data using artificial intelligence and qualitative methodology.

OBJECTIVE: Amyotrophic lateral sclerosis (ALS) is an incurable, progressive neurodegenerative diseas...

Deep learning based digital pathology for predicting treatment response to first-line PD-1 blockade in advanced gastric cancer.

BACKGROUND: Advanced unresectable gastric cancer (GC) patients were previously treated with chemothe...

Mycobactin analogue interacting with siderophore efflux-pump protein: insights from molecular dynamics simulations and whole-cell assays.

INTRODUCTION: In response to continued public health emergency of antimicrobial resistance (AMR), a ...

Predicting response to neoadjuvant chemotherapy for colorectal liver metastasis using deep learning on prechemotherapy cross-sectional imaging.

BACKGROUND AND OBJECTIVES: Deep learning models (DLMs) are applied across domains of health sciences...

Seasonal antigenic prediction of influenza A H3N2 using machine learning.

Antigenic characterization of circulating influenza A virus (IAV) isolates is routinely assessed by ...

Novel candidate genes for environmental stresses response in Synechocystis sp. PCC 6803 revealed by machine learning algorithms.

Cyanobacteria have developed acclimation strategies to adapt to harsh environments, making them a mo...

Identification of diagnostic markers related to inflammatory response and cellular senescence in endometriosis using machine learning and in vitro experiment.

OBJECTIVE: To understand the association between chronic inflammation, cellular senescence, and immu...

Assessing Endoscopic Response in Locally Advanced Rectal Cancer Treated with Total Neoadjuvant Therapy: Development and Validation of a Highly Accurate Convolutional Neural Network.

BACKGROUND: Rectal tumors display varying degrees of response to total neoadjuvant therapy (TNT). We...

Optimizing removal of antiretroviral drugs from tertiary wastewater using chlorination and AI-based prediction with response surface methodology.

Chemical and pharmaceutical chemicals found in water sources create substantial risks to human healt...

Response: Three Suggestions for Better Integrating Artificial Intelligence into Nursing Education.

Letter to the Editor Regarding Article "Prior to Initiation of Chemotherapy, Can We Predict Breast Tumor Response? Deep Learning Convolutional Neural Networks Approach Using a Breast MRI Tumor Dataset".

The cited article reports on a convolutional neural network trained to predict response to neoadjuva...

Prediction of the treatment response and local failure of patients with brain metastasis treated with stereotactic radiosurgery using machine learning: A systematic review and meta-analysis.

BACKGROUND: Stereotactic radiosurgery (SRS) effectively treats brain metastases. It can provide loca...

UNNT: A novel Utility for comparing Neural Net and Tree-based models.

The use of deep learning (DL) is steadily gaining traction in scientific challenges such as cancer r...