Bioterrorism

MLG2Net: Molecular Global Graph Network for Drug Response Prediction in Lung Cancer Cell Lines.

Drug response prediction (DRP) is a central task in the era of precision medicine. Over the past dec...

Response to Kantor's "The great automatic grammatizator: On the use and misuse of large language models in scientific and academic writing".

Integration of graph neural networks and transcriptomics analysis identify key pathways and gene signature for immunotherapy response and prognosis of skin melanoma.

OBJECTIVE: The assessment of immunotherapy plays a pivotal role in the clinical management of skin m...

Subtractive genomics approach: A guide to unveiling therapeutic targets across pathogens.

Subtractive genomics is an adaptable bioinformatics technique that is used to identify potential the...

Artificial intelligence to predict treatment response in rheumatoid arthritis and spondyloarthritis: a scoping review.

To analyse the types and applications of artificial intelligence (AI) technologies to predict treatm...

Optimizing agarase production from sp. using response surface methodology and machine learning models.

Agarase enzymes are critical in industries like food, cosmetics, and medicine where they play a crit...

Machine learning-based in-silico analysis identifies signatures of lysyl oxidases for prognostic and therapeutic response prediction in cancer.

BACKGROUND: Lysyl oxidases (LOX/LOXL1-4) are crucial for cancer progression, yet their transcription...

Cell Response to Nanoplastics and Their Carrier Effects Tracked Real-Timely with Machine Learning-Driven Smart Surface-Enhanced Raman Spectroscopy Slides.

Research on nanoplastic (NP) toxicity and their "carrier effects" on human health remains nascent, e...

Using Real-World Data for Machine-Learning Algorithms to Predict the Treatment Response in Advanced Melanoma: A Pilot Study for Personalizing Cancer Care.

PURPOSE: The use of real-world data (RWD) in oncology is becoming increasingly important for clinica...

Supervised Machine Learning and Physics Machine Learning approach for prediction of peak temperature distribution in Additive Friction Stir Deposition of Aluminium Alloy.

Additive friction stir deposition (AFSD) is a novel solid-state additive manufacturing technique tha...

Resilience response of China's terrestrial ecosystem gross primary productivity under environmental stress.

Climate change perturbations contribute to the alteration of ecosystem functions and the reduction o...

Early prediction of neoadjuvant therapy response in breast cancer using MRI-based neural networks: data from the ACRIN 6698 trial and a prospective Chinese cohort.

BACKGROUND: Early prediction of treatment response to neoadjuvant therapy (NAT) in breast cancer pat...

Positive relationship between education level and risk perception and behavioral response: A machine learning approach.

This paper aims to examine the influence mechanism of education level as a key situational factor in...

A comparative study using response surface methodology and artificial neural network for modeling the bio-reduction of hexavalent chromium (Cr⁶⁺) by immobilized cells of Paenibacillus taichungensis strain MAHA in an alginate-gellan gum matrix.

Chromium (Cr⁶⁺) waste poses a hazard as it leads to imbalanced ecosystems and severe health issues. ...

A machine learning computational approach for the mathematical anthrax disease system in animals.

OBJECTIVES: The current research investigations present the numerical solutions of the anthrax disea...

Anticancer drug response prediction integrating multi-omics pathway-based difference features and multiple deep learning techniques.

Individualized prediction of cancer drug sensitivity is of vital importance in precision medicine. W...

Integrating sensor fusion with machine learning for comprehensive assessment of phenotypic traits and drought response in poplar species.

Increased drought frequency and severity in a warming climate threaten the health and stability of f...

Multiomics evaluation and machine learning optimize molecular classification, prediction of prognosis and immunotherapy response for ovarian cancer.

BACKGROUND: Ovarian cancer (OC), owing to its substantial heterogeneity and high invasiveness, has h...

Cholera resurges in Zambia: Challenges and future directions.

Cholera remains a major global health challenge, disproportionately affecting low-income countries w...

Response to: Applicant essays and recommendation letters in residency selection: How generative artificial intelligence is changing them.

Extract optimization and biological activities of Otidea onotica using Artificial Neural Network-Genetic Algorithm and response surface methodology techniques.

In this study, the biological activities of Otidea onotica were investigated using two optimization ...