相关论文: Neural Bandits for Data Mining: Searching for Dang…

The appearance of a new dangerous and contagious disease requires the development of a drug therapy faster than what is foreseen by usual mechanisms. Many drug therapy developments consist in investigating through different clinical trials…

With increasing interest in adaptive clinical trial designs, challenges are present to drug supply chain management which may offset the benefit of adaptive designs. Thus, it is necessary to develop an optimization tool to facilitate the…

We consider incentivized exploration: a version of multi-armed bandits where the choice of arms is controlled by self-interested agents, and the algorithm can only issue recommendations. The algorithm controls the flow of information, and…

Drug repurposing is an emerging approach for drug discovery involving the reassignment of existing drugs for novel purposes. An alternative to the traditional de novo process of drug development, repurposed drugs are faster, cheaper, and…

Epilepsy is a prevalent neurological disease with millions of patients worldwide. Many patients have turned to alternative medicine due to the limited efficacy and side effects of conventional antiepileptic drugs. In this study, we…

Adverse drug interactions are a critical concern in pharmacovigilance, as both clinical trials and spontaneous reporting systems often lack the breadth to detect complex drug interactions. This study introduces a computational framework for…

Opioid overdose rates have reached an epidemic level and state-level policy innovations have followed suit in an effort to prevent overdose deaths. State-level drug law is a set of policies that may reinforce or undermine each other, and…

Mixed-integer programming (MIP) is a powerful paradigm for modeling and solving various important combinatorial optimization problems. Recently, learning-based approaches have shown a potential to speed up MIP solving via offline training…

Drug repositioning, that is finding new uses for existing drugs to treat more patients. Cumulative studies demonstrate that the mature miRNAs as well as their precursors can be targeted by small molecular drugs. At the same time, human…

Dose-finding trials are a key component of the drug development process and rely on a statistical design to help inform dosing decisions. Triallists wishing to choose a design require knowledge of operating characteristics of competing…

Decision-making in personalized medicine such as cancer therapy or critical care must often make choices for dosage combinations, i.e., multiple continuous treatments. Existing work for this task has modeled the effect of multiple…

Machine learning algorithms are widely used in the area of malware detection. With the growth of sample amounts, training of classification algorithms becomes more and more expensive. In addition, training data sets may contain redundant or…

Adverse Drug Reactions (ADRs) are a leading cause of morbidity and mortality. Existing prediction methods rely mainly on chemical similarity, machine learning on structured databases, or isolated target profiles, but often fail to integrate…

The systematic discovery of effective drug combinations is a challenging problem in modern pharmacology, driven by the combinatorial growth of potential pairings and dosage configurations. Network medicine, modeling diseases and drugs as…

Enumerating maximal $k$-biplexes (MBPs) of a bipartite graph has been used for applications such as fraud detection. Nevertheless, there usually exists an exponential number of MBPs, which brings up two issues when enumerating MBPs, namely…

Drug combination refers to the use of two or more drugs to treat a specific disease at the same time. It is currently the mainstream way to treat complex diseases. Compared with single drugs, drug combinations have better efficacy and can…

We propose an adaptive sampling approach for multiple testing which aims to maximize statistical power while ensuring anytime false discovery control. We consider $n$ distributions whose means are partitioned by whether they are below or…

In recent decades, there has been an increase in polypharmacy, the concurrent administration of multiple drugs per patient. Studies have shown that polypharmacy is linked to adverse patient outcomes and there is interest in elucidating the…

The drug discovery and development process is a long and expensive one, costing over 1 billion USD on average per drug and taking 10-15 years. To reduce the high levels of attrition throughout the process, there has been a growing interest…

Parkinson's disease is a progressive and slowly developing neurodegenerative disease, characterized by dopaminergic neuron loss in the substantia nigra region of the brain. Despite extensive research by scientists, there is not yet a cure…