Prescriptions

Performance Comparisons of AlexNet and GoogLeNet in Cell Growth Inhibition IC50 Prediction.

Drug responses in cancer are diverse due to heterogenous genomic profiles. Drug responsiveness prediction is important in clinical response to specific cancer treatments. Recently, multi-class drug responsiveness models based on deep learning (DL) models using molecular fingerprints and mutation statuses have emerged. However, for multi-class models for drug responsiveness prediction, comparisons ...

An interaction-modeling mechanism for context-dependent Text-to-SQL translation based on heterogeneous graph aggregation.

For the context-dependent Text-to-SQL task, the generation of SQL query is placed in a multi-turn interaction scenario. Each turn of Text-to-SQL must take historical interactive information and database schema into account. Accordingly, how to encode and integrate these different types of texts (the question sentence, the corresponding SQL query, and database schema) is a tough problem. In previou...

Differences in information accessed in a pharmacologic knowledge base using a conversational agent vs traditional search methods.

INTRODUCTION: Clinicians rely on pharmacologic knowledge bases to answer medication questions and avoid potential adverse drug events. In late 2018, a...

Predicting self-intercepted medication ordering errors using machine learning.

Current approaches to understanding medication ordering errors rely on relatively small manually captured error samples. These approaches are resource...

Stiffness Preprogrammable Soft Bending Pneumatic Actuators for High-Efficient, Conformal Operation.

Soft pneumatic actuators (SPAs) are extensively investigated due to their simple control strategies for producing sophisticated motions. However, the ...

AI in drug development: a multidisciplinary perspective.

The introduction of a new drug to the commercial market follows a complex and long process that typically spans over several years and entails large m...

Human Interaction Understanding With Joint Graph Decomposition and Node Labeling.

The task of human interaction understanding involves both recognizing the action of each individual in the scene and decoding the interaction relation...

Predicting HIV drug resistance using weighted machine learning method at target protein sequence-level.

Acquired immune deficiency syndrome (AIDS) is a fatal disease caused by human immunodeficiency virus (HIV). Although 23 different drugs have been avai...

Efficient Source Camera Identification with Diversity-Enhanced Patch Selection and Deep Residual Prediction.

Source camera identification has long been a hot topic in the field of image forensics. Besides conventional feature engineering algorithms developed ...

Exploration of physiological sensors, features, and machine learning models for pain intensity estimation.

In current clinical settings, typically pain is measured by a patient's self-reported information. This subjective pain assessment results in suboptim...

The Role of Artificial Intelligence in Arrhythmia Monitoring.

Arrhythmia management has been revolutionized by the ability to monitor the cardiac rhythm in a patient's home environment in real-time using high-fid...

Emotion-Driven Analysis and Control of Human-Robot Interactions in Collaborative Applications.

The utilization of robotic systems has been increasing in the last decade. This increase has been derived by the evolvement in the computational capab...

Incremental Concept Learning via Online Generative Memory Recall.

The ability to learn more concepts from incrementally arriving data over time is essential for the development of a lifelong learning system. However,...

Machine learning liver-injuring drug interactions with non-steroidal anti-inflammatory drugs (NSAIDs) from a retrospective electronic health record (EHR) cohort.

Drug-drug interactions account for up to 30% of adverse drug reactions. Increasing prevalence of electronic health records (EHRs) offers a unique oppo...

Prediction of skin disease using a new cytological taxonomy based on cytology and pathology with deep residual learning method.

With the development of artificial intelligence, technique improvement of the classification of skin disease is addressed. However, few study concerne...

AI-based language models powering drug discovery and development.

The discovery and development of new medicines is expensive, time-consuming, and often inefficient, with many failures along the way. Powered by artif...

Binding affinity prediction for binary drug-target interactions using semi-supervised transfer learning.

In the field of drug-target interactions prediction, the majority of approaches formulated the problem as a simple binary classification task. These m...

A stacked ensemble for the detection of COVID-19 with high recall and accuracy.

The main challenges for the automatic detection of the coronavirus disease (COVID-19) from computed tomography (CT) scans of an individual are: a lack...

Analysis of cognitive impairment in schizophrenia based on machine learning: Interaction between psychological stress and immune system.

The interaction between psychological stress and immune system may be associated with the cognitive impairment of schizophrenia. To employ machine lea...

Face mask detection using deep learning: An approach to reduce risk of Coronavirus spread.

Effective strategies to restrain COVID-19 pandemic need high attention to mitigate negatively impacted communal health and global economy, with the br...