Bioterrorism

Letter to the editor: multichannel deep learning prediction of major pathological response after neoadjuvant immunochemotherapy in lung cancer: a multicenter diagnostic study.

CT-based intratumoral and peritumoral radiomics to predict the treatment response to hepatic arterial infusion chemotherapy plus lenvatinib and PD-1 in high-risk hepatocellular carcinoma cases: a multi-center study.

BACKGROUND: Noninvasive and precise tools for treatment response estimation in patients with high-ri...

A 23-gene multi-omics signature predicts prognosis and treatment response in non-small cell lung cancer.

Materiality and practicality: a response to - are clinicians ethically obligated to disclose their use of medical machine learning systems to patients?

In his recent paper Hatherley discusses four reasons given to support mandatory disclosure of the us...

Impact of metal oxides on thermal response of zirconia coated diesel engines fueled by Momordica biodiesel machine learning insights.

Biodiesel presents a favourable economic outlook and environmental benefits, yet it faces limitation...

A longitudinal cohort study uncovers plasma protein biomarkers predating clinical onset and treatment response of rheumatoid arthritis.

Rheumatoid arthritis (RA) is a systemic inflammatory condition posing challenges in identifying biom...

Sub-regional radiomics combining multichannel 2-dimensional or 3-dimensional deep learning for predicting neoadjuvant chemo-immunotherapy response in esophageal squamous cell carcinoma: a multicenter study.

This study aimed to develop and compare fusion models combining sub-regional radiomics with multicha...

Predicting Pathological Complete Response Following Neoadjuvant Therapy in Patients With Breast Cancer: Development of Machine Learning-Based Prediction Models in a Retrospective Study.

BACKGROUND: Breast cancer is the most prevalent form of cancer worldwide, with 2.3 million new diagn...

Exploring personalized neoadjuvant therapy selection strategies in breast cancer: an explainable multi-modal response model.

BACKGROUND: Neoadjuvant therapy (NAT) regimens for breast cancer are generally determined according ...

Exploration of Predictive Potential of AI-enabled Portable System in Anticancer Drug Delivery: A Comparative Study with Modified Gompertz like Biphasic Response Model.

Mathematical models are conventionally used to understand the of tumor behaviors, but they generally...

Identifying and Evaluating Salt-Tolerant Halophytes Along a Tropical Coastal Zone: Growth Response and Desalination Potential.

Littoral soils along Ghana's coastal zones, hosting diverse halophytes with multiple potential appli...

A hybrid fog-edge computing architecture for real-time health monitoring in IoMT systems with optimized latency and threat resilience.

The advancement of the Internet of Medical Things (IoMT) has transformed healthcare delivery by enab...

Predictive modeling for step II therapy response in periodontitis - model development and validation.

Steps I and II periodontal therapy is the first-line treatment for periodontal disease, but has vary...

The Application of Artificial Intelligence in Addressing Biothreats.

The advent of new technologies, particularly artificial intelligence (AI), has expanded the array of...

Identification and experimental validation of BMX as a crucial PANoptosis‑related gene for immune response in Spinal Cord Injury.

Spinal cord injury (SCI) is a debilitating neurological condition that severely impacts motor, senso...

Response to comment on "Do we need flexible machine-learning algorithms to assess the effect of long-term exposure to fine particulate matter on mortality?".

Immunodiagnostic plasma amino acid residue biomarkers detect cancer early and predict treatment response.

The immune response to tumour development is frequently targeted with therapeutics but remains large...

Integrative analysis of multi-omics data and gut microbiota composition reveals prognostic subtypes and predicts immunotherapy response in colorectal cancer using machine learning.

Colorectal cancer (CRC) exhibits substantial heterogeneity in molecular subtypes and clinical outcom...

A Network-Driven Framework for Drug Response Precision Prediction of Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is a clonal malignancy of myeloid progenitor cells that demonstrates hi...

Transformative potential of artificial intelligence in US CDC HIV interventions: balancing innovation with health privacy.

Artificial intelligence (AI) holds significant potential to transform HIV prevention and treatment t...

Attention-based multimodal deep learning for interpretable and generalizable prediction of pathological complete response in breast cancer.

BACKGROUND: Accurate prediction of pathological complete response (pCR) to neoadjuvant chemotherapy ...