AIMC Topic: Drug Therapy

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Assessing the accuracy and quality of artificial intelligence (AI) chatbot-generated responses in making patient-specific drug-therapy and healthcare-related decisions.

BMC medical informatics and decision making Dec 24, 2024
BACKGROUND: Interactive artificial intelligence tools such as ChatGPT have gained popularity, yet little is known about their reliability as a reference tool for healthcare-related information for healthcare providers and trainees. The objective of t...
Reproducibility of Results Delphi Technique Drug Therapy Humans Artificial Intelligence Clinical Decision-Making
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Local-Global Memory Neural Network for Medication Prediction.

IEEE transactions on neural networks and learning systems Apr 2, 2021
Electronic medical records (EMRs) play an important role in medical data mining and sequential data learning. In this article, we propose to use a sequential neural network with dynamic content-based memories to predict future medications, given EMRs...
Pharmaceutical Preparations Data Mining Drug Therapy Algorithms Electronic Health Records Models, Theoretical Humans Neural Networks, Computer Machine Learning
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Artificial Intelligence in Pharmacovigilance: Scoping Points to Consider.

Clinical therapeutics Jan 18, 2021
Artificial intelligence (AI), a highly interdisciplinary science, is an increasing presence in pharmacovigilance (PV). A better understanding of the scope of artificial intelligence in pharmacovigilance (AIPV) may be advantageous to more sharply defi...
Pharmacovigilance Datasets as Topic Drug Therapy Humans Artificial Intelligence Machine Learning
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A novel approach for personalized response model: deep learning with individual dropout feature ranking.

Journal of pharmacokinetics and pharmacodynamics Oct 26, 2020
Deep learning is the fastest growing field in artificial intelligence and has led to many transformative innovations in various domains. However, lack of interpretability sometimes hinders its application in hypothesis-driven domains such as biology ...
Deep Learning Treatment Outcome Models, Biological Humans Computer Simulation Precision Medicine Datasets as Topic Drug Therapy Biological Variation, Population
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Emerging Pharmacotherapy and Health Care Needs of Patients in the Age of Artificial Intelligence and Digitalization.

The Annals of pharmacotherapy May 28, 2020
Advances in the application of artificial intelligence, digitization, technology, iCloud computing, and wearable devices in health care predict an exciting future for health care professionals and our patients. Projections suggest an older, generally...
Telemedicine Digital Technology Drug Therapy Aged, 80 and over Male Decision Support Systems, Clinical Humans Artificial Intelligence Delivery of Health Care Female Aged
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Multigene signatures of responses to chemotherapy derived by biochemically-inspired machine learning.

Molecular genetics and metabolism Aug 19, 2019
Pharmacogenomic responses to chemotherapy drugs can be modeled by supervised machine learning of expression and copy number of relevant gene combinations. Such biochemical evidence can form the basis of derived gene signatures using cell line data, w...
Drug Therapy Metabolic Networks and Pathways Supervised Machine Learning Gene Dosage Transcriptome Cell Line, Tumor Urinary Bladder Neoplasms Humans Female Breast Neoplasms Gene Expression Profiling
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Methodological variations in lagged regression for detecting physiologic drug effects in EHR data.

Journal of biomedical informatics Aug 30, 2018
We studied how lagged linear regression can be used to detect the physiologic effects of drugs from data in the electronic health record (EHR). We systematically examined the effect of methodological variations ((i) time series construction, (ii) tem...
Machine Learning New York City Drug Therapy Databases, Factual Humans Reproducibility of Results Data Collection Regression Analysis Electronic Health Records Time Factors Area Under Curve ROC Curve Academic Medical Centers Pharmaceutical Preparations Linear Models
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Automated ontology generation framework powered by linked biomedical ontologies for disease-drug domain.

Computer methods and programs in biomedicine Aug 16, 2018
OBJECTIVE AND BACKGROUND: The exponential growth of the unstructured data available in biomedical literature, and Electronic Health Record (EHR), requires powerful novel technologies and architectures to unlock the information hidden in the unstructu...
Disease Drug Therapy Data Mining Algorithms Semantics Decision Support Systems, Clinical Humans Biological Ontologies Knowledge Bases Machine Learning
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Drug Repositioning by Integrating Known Disease-Gene and Drug-Target Associations in a Semi-supervised Learning Model.

Acta biotheoretica Apr 26, 2018
Computational drug repositioning has been proven as a promising and efficient strategy for discovering new uses from existing drugs. To achieve this goal, a number of computational methods have been proposed, which are based on different data sources...
Supervised Machine Learning Humans Pharmacology Software Reproducibility of Results Drug Therapy Pharmacy Drug Repositioning Computational Biology Area Under Curve Models, Statistical Pharmaceutical Preparations
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Enhancing Seasonal Influenza Surveillance: Topic Analysis of Widely Used Medicinal Drugs Using Twitter Data.

Journal of medical Internet research Sep 12, 2017
BACKGROUND: Uptake of medicinal drugs (preventive or treatment) is among the approaches used to control disease outbreaks, and therefore, it is of vital importance to be aware of the counts or frequencies of most commonly used drugs and trending topi...
Drug Therapy Disease Outbreaks Social Media Humans Influenza, Human Machine Learning Public Health
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