Prescriptions

Interactive Medical Image Segmentation Using Deep Learning With Image-Specific Fine Tuning.

Convolutional neural networks (CNNs) have achieved state-of-the-art performance for automatic medical image segmentation. However, they have not demonstrated sufficiently accurate and robust results for clinical use. In addition, they are limited by the lack of image-specific adaptation and the lack of generalizability to previously unseen object classes (a.k.a. zero-shot learning). To address the...

Nonlinear System Identification Based on Convolutional Neural Networks for Multiple Drug Interactions.

In heart failure patients, hemodynamics can be regulated by therapeutic drugs. Although the cardiovascular responses to these drugs usually include nonlinearity and drug interactions, it is difficult to identify the characteristics of the dynamics under such conditions. This study, therefore, was aimed at evaluating the technique used for nonlinear system identification based on convolutional neur...

Deep Learning for Medication Assessment of Individuals with Parkinson's Disease Using Wearable Sensors.

Motor fluctuations between "OFF" state (with no benefit from medication) and " ON" state (with optimum benefit from medication) are a major focus of c...

Comparing Physical Human-Robot Interaction with Spring-and Elastomer-Based Series Elastic Actuators.

Physical human-robot interaction (pHRI) is an important consideration in the design of rehabilitation exoskeletons. Series Elastic Actuators (SEAs) ar...

Medhere: A Smartwatch-based Medication Adherence Monitoring System using Machine Learning and Distributed Computing.

Poor medication adherence threatens an individual's health and is responsible for substantial medical costs in the United States annually. In order to...

Using Unsupervised Machine Learning to Identify Subgroups Among Home Health Patients With Heart Failure Using Telehealth.

This study explored the use of unsupervised machine learning to identify subgroups of patients with heart failure who used telehealth services in the ...

[Artificial Intelligence in Drug Discovery].

According to the increase of data generated from analytical instruments, application of artificial intelligence(AI)technology in medical field is indi...

Drug-drug interaction extraction via hierarchical RNNs on sequence and shortest dependency paths.

MOTIVATION: Adverse events resulting from drug-drug interactions (DDI) pose a serious health issue. The ability to automatically extract DDIs describe...

A postprocessing method in the HMC framework for predicting gene function based on biological instrumental data.

Predicting gene function based on biological instrumental data is a complicated and challenging hierarchical multi-label classification (HMC) problem....

Using Natural Language Processing of Free-Text Radiology Reports to Identify Type 1 Modic Endplate Changes.

Electronic medical record (EMR) systems provide easy access to radiology reports and offer great potential to support quality improvement efforts and ...

SuperDRUG2: a one stop resource for approved/marketed drugs.

Regular monitoring of drug regulatory agency web sites and similar resources for information on new drug approvals and changes to legal status of mark...

Electronic Health Record Phenotypes for Precision Medicine: Perspectives and Caveats From Treatment of Breast Cancer at a Single Institution.

Precision medicine is at the forefront of biomedical research. Cancer registries provide rich perspectives and electronic health records (EHRs) are co...

Prediction of Drug-Plasma Protein Binding Using Artificial Intelligence Based Algorithms.

AIM AND OBJECTIVE: Plasma protein binding (PPB) has vital importance in the characterization of drug distribution in the systemic circulation. Unfavor...

Head Motion and Head Gesture-Based Robot Control: A Usability Study.

The assistive robot system adaptive head motion control for user-friendly support (AMiCUS) has been developed to increase the autonomy of motion impai...

Network pharmacology-based analysis of Chinese herbal Naodesheng formula for application to Alzheimer's disease.

Naodesheng (NDS) formula, which consists of Rhizoma Chuanxiong, Lobed Kudzuvine, Carthamus tinctorius, Radix Notoginseng, and Crataegus pinnatifida, i...

Prediction of Human Drug Targets and Their Interactions Using Machine Learning Methods: Current and Future Perspectives.

Identification of drug targets and drug target interactions are important steps in the drug-discovery pipeline. Successful computational prediction me...

3000PA-Towards a National Reference Corpus of German Clinical Language.

We introduce 3000PA, a clinical document corpus composed of 3,000 EPRs from three different clinical sites, which will serve as the backbone of a nati...

Combining the Generic Entity-Attribute-Value Model and Terminological Models into a Common Ontology to Enable Data Integration and Decision Support.

The integration of clinical information models and termino-ontological models into a unique ontological framework is highly desirable for it facilitat...

[Machine Learning-based Prediction of Seizure-inducing Action as an Adverse Drug Effect].

　During the preclinical research period of drug development, animal testing is widely used to help screen out a drug's dangerous side effects. However...

Structuring Clinical Decision Support Rules for Drug Safety Using Natural Language Processing.

Drug safety is an important aspect in healthcare, resulting in a number of inadvertent events, which may harm the patients. IT based Clinical Decision...