Latest AI and machine learning research in prescriptions for healthcare professionals.
INTRODUCTION: Nonmedical use of prescription medications/drugs (NMUPD) is a serious public health threat, particularly in relation to the prescription opioid analgesics abuse epidemic. While attention to this problem has been growing, there remains an urgent need to develop novel strategies in the field of "digital epidemiology" to better identify, analyze and understand trends in NMUPD behavior.
Statistical analysis was performed on physicochemical descriptors of ∼250 drugs known to interact with one or more SLC22 "drug" transporters (i.e., SLC22A6 or OAT1, SLC22A8 or OAT3, SLC22A1 or OCT1, and SLC22A2 or OCT2), followed by application of machine-learning methods and wet laboratory testing of novel predictions. In addition to molecular charge, organic anion transporters (OATs) were found ...
This paper presents a novel approach to fruit detection using deep convolutional neural networks. The aim is to build an accurate, fast and reliable f...
Identifying biomarker genes and characterizing interaction pathways with high-dimensional and low-sample size microarray data is a major challenge in ...
In association studies, the combined effects of single nucleotide polymorphism (SNP)-SNP interactions and the problem of imbalanced data between cases...
Organic matters (OMs) and their oxidization products often influence the fate and transport of heavy metals in the subsurface aqueous systems through ...
Identification and analysis of host-pathogen interactions (HPI) is essential to study infectious diseases. However, HPI data are sparse in existing mo...
Tacrolimus is a potent immunosuppressant; however, it suffers from several problems such as poor water solubility (4-12 μg/mL), low and variable oral ...
Drug toxicity is a major concern for both regulatory agencies and the pharmaceutical industry. In this context, text-mining methods for the identifica...
A machine learning method called kriging is applied to the set of all 20 naturally occurring amino acids. Kriging models are built that predict electr...
Aim of the present study was to assess the hepatoprotective activity of goat milk on antitubercular drug-induced hepatotoxicity in rats. Hepatotoxicit...
The brain can reproduce memories from partial data; this ability is critical for memory recall. The process of memory recall has been studied using au...
Swarm robotics is concerned with the decentralised coordination of multiple robots having only limited communication and interaction abilities. Althou...
Interest in stimulus responsive materials and polymers has grown over the years, having shown great promise in a diverse set of applications. For drug...
Identifying protein-protein interactions is important in molecular biology. Experimental methods to this issue have their limitations, and computation...
Protein-protein interaction (PPI) plays a key role in understanding cellular mechanisms in different organisms. Many supervised classifiers like Rando...
Medicinal chemistry patents contain rich information about chemical compounds. Although much effort has been devoted to extracting chemical entities f...
Since the late 1990s, there has been a burst of research on robotic devices for poststroke rehabilitation. Robot-mediated therapy produced improvement...
BACKGROUND: Both ginsenoside Re and B-complex vitamins are widely used as nutritional supplements. They are often taken together so as to fully utiliz...
Objective. The aim of this exploratory pilot study is to test the effects of bilateral tDCS combined with upper extremity robot-assisted therapy (RAT)...