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Predicting clinical outcomes to anti-cancer drugs on a personalized basis is challenging in cancer treatment due to the heterogeneity of tumors. Traditional computational efforts have been made to model the effect of drug response on…

Machine Learning · Computer Science 2022-07-12 Jie Gao , Jing Hu , Wanqing Sun , Yili Shen , Xiaonan Zhang , Xiaomin Fang , Fan Wang , Guodong Zhao

According to Jerne's idiotypic network hypothesis, the adaptive immune system is regulated by interactions between the variable regions of antibodies, B cells, and T cells.1 The symmetrical immune network theory2,3 is based on Jerne's…

Cell Behavior · Quantitative Biology 2014-03-07 Earnest Leung , Geoffrey W. Hoffmann

The increased affordability of whole genome sequencing has motivated its use for phenotypic studies. We address the problem of learning interpretable models for discrete phenotypes from whole genomes. We propose a general approach that…

In the UK, approximately 400,000 people with type 1 diabetes (T1D) rely on insulin delivery due to insufficient pancreatic insulin production. Managing blood glucose (BG) levels is crucial, with continuous glucose monitoring (CGM) playing a…

Machine Learning · Computer Science 2023-12-21 Chengzhe Piao , Ken Li

Cytotoxic T-lymphocytes (CTLs) recognize viral protein fragments displayed by major histocompatibility complex (MHC) molecules on the surface of virally infected cells and generate an anti-viral response that can kill the infected cells.…

Populations and Evolution · Quantitative Biology 2014-03-25 Taylor A. Kessinger , Alan S. Perelson , Richard A. Neher

Type 1 Diabetes (T1D) affects millions worldwide, requiring continuous monitoring to prevent severe hypo- and hyperglycemic events. While continuous glucose monitoring has improved blood glucose management, deploying predictive models on…

Machine Learning · Computer Science 2025-11-27 Mirko Paolo Barbato , Giorgia Rigamonti , Davide Marelli , Paolo Napoletano

The specific region of an antibody responsible for binding to an antigen, known as the paratope, is essential for immune recognition. Accurate identification of this small yet critical region can accelerate the development of therapeutic…

Biomolecules · Quantitative Biology 2025-10-08 Gabriel Athènes , Adam Woolfe , Thierry Mora , Aleksandra M. Walczak

Identifying a patient's key problems over time is a common task for providers at the point care, yet a complex and time-consuming activity given current electric health records. To enable a problem-oriented summarizer to identify a…

Applications · Statistics 2020-03-26 Gal Levy-Fix , Jason Zucker , Konstantin Stojanovic , Noémie Elhadad

Assessment of circulating CD4 count change over time in HIV-infected subjects on antiretroviral therapy (ART) is a central component of disease monitoring. The increasing number of HIV-infected subjects starting therapy and the limited…

In epidemiological studies, the capture-recapture (CRC) method is a powerful tool that can be used to estimate the number of diseased cases or potentially disease prevalence based on data from overlapping surveillance systems. Estimators…

Applications · Statistics 2023-06-21 Yuzi Zhang , Lin Ge , Lance A. Waller , Robert H. Lyles

Medication recommendation is a crucial task in healthcare, especially for patients with complex medical conditions. However, existing methods often struggle to effectively balance the reuse of historical medications with the introduction of…

Artificial Intelligence · Computer Science 2025-07-08 Feiyue Wu , Tianxing Wu , Shenqi Jing

Antimicrobial resistance is becoming a major threat to public health throughout the world. Researchers are attempting to contrast it by developing both new antibiotics and patient-specific treatments. In the second case, whole-genome…

Applications · Statistics 2023-07-25 Clara Grazian

The diversity of T-cell receptors recognizing foreign pathogens is generated through a highly stochastic recombination process, making the independent production of the same sequence rare. Yet unrelated individuals do share receptors, which…

In this paper we investigate the use of model-based reinforcement learning to assist people with Type 1 Diabetes with insulin dose decisions. The proposed architecture consists of multiple Echo State Networks to predict blood glucose levels…

In this paper we made a review of some papers about probabilistic regulatory networks (PRN), in particular we introduce our concept of homomorphisms of PRN with an example of projection of a regulatory network to a smaller one. We apply the…

Cell Behavior · Quantitative Biology 2007-08-20 Maria A. Avino-Diaz

Despite extensive safety assessments of drugs prior to their introduction to the market, certain adverse drug reactions (ADRs) remain undetected. The primary objective of pharmacovigilance is to identify these ADRs (i.e., signals). In…

Methodology · Statistics 2024-04-23 Louis Dijkstra , Tania Schink , Ronja Foraita

Red blood cells are highly deformable and present in various shapes. In blood cell disorders, only a subset of all cells is morphologically altered and relevant for the diagnosis. However, manually labeling of all cells is laborious,…

Computer Vision and Pattern Recognition · Computer Science 2020-07-24 Ario Sadafi , Asya Makhro , Anna Bogdanova , Nassir Navab , Tingying Peng , Shadi Albarqouni , Carsten Marr

Type 1 diabetes is a serious disease in which individuals are unable to regulate their blood glucose levels, leading to various medical complications. Artificial pancreas (AP) systems have been developed as a solution for type 1 diabetic…

Signal Processing · Electrical Eng. & Systems 2023-05-18 Ke Ma , Hongkai Chen , Shan Lin

An unsolved challenge in the development of antigen specific immunotherapies is determining the optimal antigens to target. Comprehension of antigen-MHC binding is paramount towards achieving this goal. Here, we present CASTELO, a combined…

Quantitative Methods · Quantitative Biology 2020-12-09 David Bell , Giacomo Domeniconi , Chih-Chieh Yang , Ruhong Zhou , Leili Zhang , Guojing Cong

Type 1 Diabetes (T1D) management is a complex task due to many variability factors. Artificial Pancreas (AP) systems have alleviated patient burden by automating insulin delivery through advanced control algorithms. However, the…

Machine Learning · Computer Science 2025-11-03 Stefano De Carli , Nicola Licini , Davide Previtali , Fabio Previdi , Antonio Ferramosca