Nicotinamide phosphoribosyltransferase (NAMPT) inhibitors show importance in cancer
disease treatment while selecting compounds from a library according to inhibitory potency …

Cancer drug response prediction is the fundamental task in precision medicine, which
provides opportunities for cancer therapy. Several methods have been proposed to screen …

Cancer research has increasingly utilized multi-omics analysis in recent decades to obtain
biomolecular information from multiple layers, thereby gaining a better understanding of …

Both FCM and PCM clustering methods have been widely applied to pattern recognition and
data clustering. Nevertheless, FCM is sensitive to noise and PCM occasionally generates …

Simple Summary Medical gas plasma is a new modality in cancer treatment showing
favorable results in preclinical and clinical trials; however, the cascade of molecular events …

Patients with the target gene mutation frequently derive significant clinical benefits from
target therapy. However, differences in the abundance level of mutations among patients …

Despite their satisfactory performance, most existing listwise Learning-To-Rank (LTR)
models do not consider the crucial issue of robustness. A data set can be contaminated in …

Background Predictive models utilizing social determinants of health (SDH), demographic
data, and local weather data were trained to predict missed imaging appointments (MIA) …

Personalized drug response prediction is an approach for tailoring effective therapeutic
strategies for patients based on their tumors' genomic characterization. While machine …

Despite their empirical success, most existing listwiselearning-to-rank (LTR) models are not
built to be robust to errors in labeling or annotation, distributional data shift, or adversarial …