Results 161 to 170 of about 137,667 (314)
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source
Approximate Bayesian computation design for phase I clinical trials. [PDF]
Jin H, Du W, Yin G.
europepmc +1 more source
ABSTRACT The muscle capsule of Trichinella is a critical structure that impedes immune attacks and drug penetration, yet the molecular mechanisms underlying its formation remain poorly understood. Using a high‐quality super‐pangenome comprising 12 Trichinella species, we compared extensive genomic variations between encapsulating and non‐encapsulating ...
Qingbo Lv +8 more
wiley +1 more source
Convolutional Neural Networks as Summary Statistics for Approximate Bayesian Computation. [PDF]
AKesson M +3 more
europepmc +1 more source
Scalable Approximate Bayesian Computation for Growing Network Models via\n Extrapolated and Sampled Summaries [PDF]
Louis Raynal +3 more
openalex +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
Microsimulation Model Calibration with Approximate Bayesian Computation in R: A Tutorial. [PDF]
Shewmaker P +4 more
europepmc +1 more source
DIYABC v2.0: a software to make approximate Bayesian computation inferences about population history using single nucleotide polymorphism, DNA sequence and microsatellite data [PDF]
Jean‐Marie Cornuet +7 more
openalex +1 more source
It is innovatively utilized single‐cell RNA sequencing to explore the underlying causes of diabetes mellitus‐induced erectile dysfunction, followed by machine learning‐driven design of a single‐atom nanozyme (Fe‐DMOF) for precision treatment of erectile dysfunction.
Xiang Zhou +8 more
wiley +1 more source

