Bioterrorism

Large-scale deep learning identifies the antiviral potential of PKI-179 and MTI-31 against coronaviruses.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to the global pandemic of Coron...

Pretreatment CT-based machine learning radiomics model predicts response in unresectable hepatocellular carcinoma treated with lenvatinib plus PD-1 inhibitors and interventional therapy.

Artificial Intelligence Large Language Models Address Anterior Cruciate Ligament Reconstruction: Superior Clarity and Completeness by Gemini Compared With ChatGPT-4 in Response to American Academy of Orthopaedic Surgeons Clinical Practice Guidelines.

PURPOSE: To assess the ability of ChatGPT-4 and Gemini to generate accurate and relevant responses t...

Optimization of fungal secondary metabolites production via response surface methodology coupled with multi-parameter optimized artificial neural network model.

Filamentous fungi's secondary metabolites (SMs) possess significant application owing to their disti...

Towards regulatory generative AI in ophthalmology healthcare: a security and privacy perspective.

As the healthcare community increasingly harnesses the power of generative artificial intelligence (...

Whole slide image-based weakly supervised deep learning for predicting major pathological response in non-small cell lung cancer following neoadjuvant chemoimmunotherapy: a multicenter, retrospective, cohort study.

OBJECTIVE: Develop a predictive model utilizing weakly supervised deep learning techniques to accura...

Instrumented timed up and go test and machine learning-based levodopa response evaluation: a pilot study.

BACKGROUND: The acute levodopa challenge test (ALCT) is a universal method for evaluating levodopa r...

Using deep learning and pretreatment EEG to predict response to sertraline, bupropion, and placebo.

OBJECTIVE: Predicting an individual's response to antidepressant medication remains one of the most ...

A multi-task deep learning model based on comprehensive feature integration and self-attention mechanism for predicting response to anti-PD1/PD-L1.

BACKGROUND: Immune checkpoint inhibitor (ICI) has been widely used in the treatment of advanced canc...

Integrating respiratory microbiome and host immune response through machine learning for respiratory tract infection diagnosis.

At present, the diagnosis of lower respiratory tract infections (LRTIs) is difficult, and there is a...

A Preliminary Study to Evaluate the Immune Response to a Booster Dose of the Adult Tetanus-Diphtheria Vaccine (Td) Available in Iran.

BACKGROUND: Despite the availability of tetanus-diphtheria (TD) vaccines in Iran, the seroconversion...

Preoperative treatment response prediction for pancreatic cancer by multiple microRNAs in plasma exosomes: Optimization using machine learning and network analysis.

BACKGROUND/OBJECTIVES: MicroRNAs (miRNAs) are involved in chemosensitivity through their biological ...

Sampled-data synchronization for fuzzy inertial cellular neural networks and its application in secure communication.

This paper designs the sampled-data control (SDC) scheme to delve into the synchronization problem o...

ABR-Attention: An Attention-Based Model for Precisely Localizing Auditory Brainstem Response.

Auditory Brainstem Response (ABR) is an evoked potential in the brainstem's neural centers in respon...

Non-invasive multimodal CT deep learning biomarker to predict pathological complete response of non-small cell lung cancer following neoadjuvant immunochemotherapy: a multicenter study.

OBJECTIVES: Although neoadjuvant immunochemotherapy has been widely applied in non-small cell lung c...

Magnetic Resonance-Guided Cancer Therapy Radiomics and Machine Learning Models for Response Prediction.

Magnetic resonance imaging (MRI) is known for its accurate soft tissue delineation of tumors and nor...

MCMVDRP: a multi-channel multi-view deep learning framework for cancer drug response prediction.

Drug therapy remains the primary approach to treating tumours. Variability among cancer patients, in...

Predicting Response to Neuromodulators or Prokinetics in Patients With Suspected Gastroparesis Using Machine Learning: The "BMI, Infectious Prodrome, Delayed GES, and No Diabetes" Model.

INTRODUCTION: Pharmacologic therapies for symptoms of gastroparesis (GP) have limited efficacy, and ...

A commentary on 'Single-cell and bulk RNA-sequence identified fibroblasts signature and CD8 + T cell - fibroblast subtype predicting prognosis and immune therapeutic response of bladder cancer, based on machine-learning'.

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...