Prescriptions

Big data-driven intelligent governance of college students' physical health: System and strategy.

With the development of information technology, the application of a new generation of information technologies, such as big data, Internet Plus, and artificial intelligence, in the sports field is an emerging, novel trend. This paper examined the relevant research results and literature on physical education, computer science, pedagogy, management, and other disciplines, then used a self-made que...

Inferring Drug-Target Interactions Based on Random Walk and Convolutional Neural Network.

Computational strategies for identifying new drug-target interactions (DTIs) can guide the process of drug discovery, reduce the cost and time of drug development, and thus promote drug development. Most recently proposed methods predict DTIs via integration of heterogeneous data related to drugs and proteins. However, previous methods have failed to deeply integrate these heterogeneous data and l...

A Comprehensive Review of Computational Methods For Drug-Drug Interaction Detection.

The detection of drug-drug interactions (DDIs) is a crucial task for drug safety surveillance, which provides effective and safe co-prescriptions of m...

MatchMaker: A Deep Learning Framework for Drug Synergy Prediction.

Drug combination therapies have been a viable strategy for the treatment of complex diseases such as cancer due to increased efficacy and reduced side...

The effects of robotic assistance on upper limb spatial muscle synergies in healthy people during planar upper-limb training.

BACKGROUND: Robotic rehabilitation is a commonly adopted technique used to restore motor functionality of neurological patients. However, despite prom...

Innovative Application of Artificial Intelligence in the Field of Innovation and Entrepreneurship of College Students in Internet Colleges and Universities.

With the promotion and development of artificial intelligence, the computer major has become a hot major in innovation and entrepreneurship education....

The Patient Matters in the End(point).

Digital health technologies such as wearable sensors are increasingly being used in clinical trials. However, the endpoints created from these useful ...

Deep learning for topical trend discovery in online discourse about Pre-Exposure Prophylaxis (PrEP).

Pre-Exposure Prophylaxis (PrEP) interventions are increasingly prevalent on social media. These data can be mined for insights about PrEP that may not...

Effective deep learning for oral exfoliative cytology classification.

The use of sharpness aware minimization (SAM) as an optimizer that achieves high performance for convolutional neural networks (CNNs) is attracting at...

Antistroke Network Pharmacological Prediction of Xiaoshuan Tongluo Recipe Based on Drug-Target Interaction Based on Deep Learning.

Stroke is a common cerebrovascular disease that threatens human health, and the search for therapeutic drugs is the key to treatment. New drug discove...

Transfer learning based generalized framework for state of health estimation of Li-ion cells.

Estimating the state of health (SOH) of batteries powering electronic devices in real-time while in use is a necessity. The applicability of most of t...

CSatDTA: Prediction of Drug-Target Binding Affinity Using Convolution Model with Self-Attention.

Drug discovery, which aids to identify potential novel treatments, entails a broad range of fields of science, including chemistry, pharmacology, and ...

Assessment of Physical Fitness and Health Status of Athletes Based on Intelligent Medical Treatment under Machine Learning.

Machine learning is an interdisciplinary study of how to make computer programs perform similar to human learning, and its techniques are widely used ...

Human-like behavioral variability blurs the distinction between a human and a machine in a nonverbal Turing test.

Variability is a property of biological systems, and in animals (including humans), behavioral variability is characterized by certain features, such ...

Evaluating Ensemble Learning Methods for Multi-Modal Emotion Recognition Using Sensor Data Fusion.

Automatic recognition of human emotions is not a trivial process. There are many factors affecting emotions internally and externally. Expressing emot...

Is attention branch network effective in classifying dental implants from panoramic radiograph images by deep learning?

Attention mechanism, which is a means of determining which part of the forced data is emphasized, has attracted attention in various fields of deep le...

Language-agnostic pharmacovigilant text mining to elicit side effects from clinical notes and hospital medication records.

We sought to craft a drug safety signalling pipeline associating latent information in clinical free text with exposures to single drugs and drug pair...

Utilizing Deep Learning for Detecting Adverse Drug Events in Structured and Unstructured Regulatory Drug Data Sets.

BACKGROUND: The US Food and Drug Administration (FDA) collects and retains several data sets on post-market drugs and associated adverse events (AEs)....

Matrix factorization with denoising autoencoders for prediction of drug-target interactions.

Drug-target interaction is crucial in the discovery of new drugs. Computational methods can be used to identify new drug-target interactions at low co...

Drug Metabolism: A Half-Century Plus of Progress, Continued Needs, and New Opportunities.

The systematic study of drug metabolism began in the 19th Century, but most of what we know now has been learned in the last 50 years. Drug metabolism...