AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Drug Prescriptions

Showing 21 to 30 of 38 articles

Clear Filters

Neural network analysis of Chinese herbal medicine prescriptions for patients with colorectal cancer.

Complementary therapies in medicine
Traditional Chinese Medicine (TCM) is an experiential form of medicine with a history dating back thousands of years. The present study aimed to utilize neural network analysis to examine specific prescriptions for colorectal cancer (CRC) in clinical...

Learning Doctors' Medicine Prescription Pattern for Chronic Disease Treatment by Mining Electronic Health Records: A Multi-Task Learning Approach.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Increasing learning ability from massive medical data and building learning methods robust to data quality issues are key factors toward building data-driven clinical decision support systems for medicine prescription decision support. Here, we attem...

Deep Learning Solutions for Classifying Patients on Opioid Use.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Opioid analgesics, as commonly prescribed medications used for relieving pain in patients, are especially prevalent in US these years. However, an increasing amount of opioid misuse and abuse have caused lots of consequences. Researchers and clinicia...

FABLE: A Semi-Supervised Prescription Information Extraction System.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Prescription information is an important component of electronic health records (EHRs). This information contains detailed medication instructions that are crucial for patients' well-being and is often detailed in the narrative portions of EHRs. As a...

Personalized prediction of drug efficacy for diabetes treatment via patient-level sequential modeling with neural networks.

Artificial intelligence in medicine
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...

Using drug knowledgebase information to distinguish between look-alike-sound-alike drugs.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To extract drug indications from a commercial drug knowledgebase and determine to what extent drug indications can discriminate between look-alike-sound-alike (LASA) drugs.

Robotic dispensing improves patient safety, inventory management, and staff satisfaction in an outpatient hospital pharmacy.

Journal of evaluation in clinical practice
RATIONALE, AIMS AND OBJECTIVES: Implementation of robotic systems in outpatient hospital pharmacies is uncommon. Other than cost, 1 of the barriers to widespread adoption is the lack of definitive evidence that this technology actually reduces dispen...

Predicting inadequate postoperative pain management in depressed patients: A machine learning approach.

PloS one
Widely-prescribed prodrug opioids (e.g., hydrocodone) require conversion by liver enzyme CYP-2D6 to exert their analgesic effects. The most commonly prescribed antidepressant, selective serotonin reuptake inhibitors (SSRIs), inhibits CYP-2D6 activity...

Machine learning for prediction of sustained opioid prescription after anterior cervical discectomy and fusion.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: The severity of the opioid epidemic has increased scrutiny of opioid prescribing practices. Spine surgery is a high-risk episode for sustained postoperative opioid prescription.