AIMC Topic: Drug Prescriptions
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Personalized prediction of drug efficacy for diabetes treatment via patient-level sequential modeling with neural networks.
Artificial intelligence in medicine
Feb 23, 2018
Patients with type 2 diabetes mellitus are generally under continuous long-term medical treatment based on anti-diabetic drugs to achieve the desired glucose level. Thus, each patient is associated with a sequence of multiple records for prescription...
An ontology-driven clinical decision support system (IDDAP) for infectious disease diagnosis and antibiotic prescription.
Artificial intelligence in medicine
Feb 9, 2018
BACKGROUND: The available antibiotic decision-making systems were developed from a physician's perspective. However, because infectious diseases are common, many patients desire access to knowledge via a search engine. Although the use of antibiotics...
Drug Prescriptions
Drug Therapy, Computer-Assisted
Decision Support Systems, Clinical
Bacterial Infections
Predictive Value of Tests
Biological Ontologies
Humans
Machine Learning
Decision Support Techniques
Anti-Bacterial Agents
Clinical Decision-Making
Reproducibility of Results
Diagnosis, Computer-Assisted
User-Computer Interface
ROC Curve
Primary Care Provider Perceptions and Practices Regarding Dosing Units for Oral Liquid Medications.
Academic pediatrics
Dec 18, 2017
INTRODUCTION: To prevent errors, health care professional and safety organizations recommend using milliliters (mL) alone for oral liquid medication dosing instructions and devices. In 2018, for federal incentives under the Quality Payment Program, o...
Physicians, Family
Pharmaceutical Preparations
Male
Administration, Oral
Humans
Middle Aged
Electronic Prescribing
Physicians, Primary Care
Electronic Health Records
Surveys and Questionnaires
Internal Medicine
Drug Prescriptions
Female
Attitude of Health Personnel
Medication Errors
Adult
Nurse Practitioners
Pediatricians
Sex differences in drugs: the development of a comprehensive knowledge base to improve gender awareness prescribing.
Biology of sex differences
Oct 24, 2017
Identifying Drug-Drug Interactions by Data Mining: A Pilot Study of Warfarin-Associated Drug Interactions.
Circulation. Cardiovascular quality and outcomes
Nov 8, 2016
BACKGROUND: Knowledge about drug-drug interactions commonly arises from preclinical trials, from adverse drug reports, or based on knowledge of mechanisms of action. Our aim was to investigate whether drug-drug interactions were discoverable without ...
Female
Risk Factors
Aged
Aged, 80 and over
Male
Humans
Machine Learning
Retrospective Studies
Blood Coagulation
Warfarin
International Normalized Ratio
Registries
Drug Interactions
Pilot Projects
Logistic Models
Predictive Value of Tests
Anticoagulants
Data Mining
Atrial Fibrillation
Drug Prescriptions
Administrative Claims, Healthcare
Polypharmacy
An end-to-end hybrid algorithm for automated medication discrepancy detection.
BMC medical informatics and decision making
May 6, 2015
BACKGROUND: In this study we implemented and developed state-of-the-art machine learning (ML) and natural language processing (NLP) technologies and built a computerized algorithm for medication reconciliation. Our specific aims are: (1) to develop a...
Chronic Pain Prevalence, Opioid Use, and Primary Care Provider Opioid Prescription Patterns in the U.S. from 2017 to 2019 Derived from Medicaid Claims Data.
Studies in health technology and informatics
Aug 7, 2025
Chronic non-cancer pain (CNCP) is a major health concern in the United States, incurring substantial healthcare costs and frequently requiring opioid therapy in primary care. This retrospective cross-sectional study used Medicaid claims data from six...
Use of an Untrained Large Language Model for Antibiotic Prescription in Pediatric Infectious Diseases at Primary Care Settings: A Study From the Italian Society for Pediatric Infectious Diseases.
The Pediatric infectious disease journal
Jun 1, 2025
The development of artificial intelligence systems is revolutionizing many fields of medicine, but specific studies are still missing in pediatrics. In our study, we showed that an untrained free-to-use large language model provided reliable response...
GP or ChatGPT? Ability of large language models (LLMs) to support general practitioners when prescribing antibiotics.
The Journal of antimicrobial chemotherapy
May 2, 2025
INTRODUCTION: Large language models (LLMs) are becoming ubiquitous and widely implemented. LLMs could also be used for diagnosis and treatment. National antibiotic prescribing guidelines are customized and informed by local laboratory data on antimic...
Identifying high-dose opioid prescription risks using machine learning: A focus on sociodemographic characteristics.
Journal of opioid management
Jan 1, 2025
OBJECTIVE: The objective of this study was to leverage machine learning techniques to analyze administrative claims and socioeconomic data, with the aim of identifying and interpreting the risk factors associated with high-dose opioid prescribing.
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