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Prescriptions

Latest AI and machine learning research in prescriptions for healthcare professionals.

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Showing 820-840 of 6,782 articles
Deep learning large-scale drug discovery and repurposing.

Large-scale drug discovery and repurposing is challenging. Identifying the mechanism of action (MOA)...

Through a computer monitor darkly: artificial intelligence in absorption, distribution, metabolism and excretion science.

Artificial Intelligence (AI) is poised or has already begun to influence absorption, distribution, m...

NABNet: Deep Learning-Based IoT Alert System for Detection of Abnormal Neck Behavior.

The excessive use of electronic devices for prolonged periods has led to problems such as neck pain ...

Breaking the silence: leveraging social interaction data to identify high-risk suicide users online using network analysis and machine learning.

Suicidal thought and behavior (STB) is highly stigmatized and taboo. Prone to censorship, yet pervas...

X-ray absorption spectroscopy combined with deep learning for auto and rapid illicit drug detection.

X-ray absorption spectroscopy (XAS) is a widely used substance analysis technique. It bases on the ...

Artificial intelligence and prescription of antibiotic therapy: present and future.

INTRODUCTION: In the past few years, the use of artificial intelligence in healthcare has grown expo...

Machine Learning Methods for Precision Dosing in Anticancer Drug Therapy: A Scoping Review.

INTRODUCTION: In the last decade, various Machine Learning techniques have been proposed aiming to i...

Predicting the Healing of Lower Extremity Fractures Using Wearable Ground Reaction Force Sensors and Machine Learning.

Lower extremity fractures pose challenges due to prolonged healing times and limited assessment meth...

Chemical analogue based drug design for cancer treatment targeting PI3K: integrating machine learning and molecular modeling.

Cancer is a generic term for a group of disorders defined by uncontrolled cell growth and the potent...

MalariaFlow: A comprehensive deep learning platform for multistage phenotypic antimalarial drug discovery.

Malaria remains a significant global health challenge due to the growing drug resistance of Plasmodi...

Integration of Animal Behavioral Assessment and Convolutional Neural Network to Study Wasabi-Alcohol Taste-Smell Interaction.

The commercial wasabi pastes commonly used for food preparation contain a homologous compound of che...

Light-Driven Microrobots for Targeted Drug Delivery.

As a new micromanipulation tool with the advantages of small size, flexible movement and easy manipu...

Decoding IBS: a machine learning approach to psychological distress and gut-brain interaction.

PURPOSE: Irritable bowel syndrome (IBS) is a diagnosis defined by gastrointestinal (GI) symptoms lik...

Identification of medication-related fall risk in adults and older adults admitted to hospital: A machine learning approach.

The study aimed to develop and validate, through machine learning, a fall risk prediction model rela...

FLAT: Fusing layer representations for more efficient transfer learning in NLP.

Parameter efficient transfer learning (PETL) methods provide an efficient alternative for fine-tunin...

MGNDTI: A Drug-Target Interaction Prediction Framework Based on Multimodal Representation Learning and the Gating Mechanism.

Drug-Target Interaction (DTI) prediction facilitates acceleration of drug discovery and promotes dru...

Rapid Identification of Drug Mechanisms with Deep Learning-Based Multichannel Surface-Enhanced Raman Spectroscopy.

Rapid identification of drug mechanisms is vital to the development and effective use of chemotherap...

Machine learning of Raman spectra predicts drug release from polysaccharide coatings for targeted colonic delivery.

Colonic drug delivery offers numerous pharmaceutical opportunities, including direct access to local...

Sea Horse Optimization-Deep Neural Network: A Medication Adherence Monitoring System Based on Hand Gesture Recognition.

Medication adherence is an essential aspect of healthcare for patients and is important for achievin...

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