Using machine learning methods to predict all-cause somatic hospitalizations in adults: A systematic review.

Aim: In this review, we investigated how Machine Learning (ML) was utilized to predict all-cause somatic hospital admissions and readmissions in adults.

Methods: We searched eight databases (PubMed, Embase, Web of Science, CINAHL, ProQuest, OpenGrey, WorldCat, and MedNar) from their inception date to October 2023, and included records that predicted all-cause somatic hospital admissions and readmissions of adults using ML methodology. We used the CHARMS checklist for data extraction, PROBAST for bias and applicability assessment, and TRIPOD for reporting quality.

Short-term learning effect of ChatGPT on pharmacy students' learning.

Introduction: Students in pharmacy are positive towards integrating artificial intelligence and ChatGPT into their practice. The aim of this study was to investigate the direct short-term learning effect of using Chat GPT by pharmacy students.

Methods: This was an experimental randomized study.

"Using network analysis modularity to group health code systems and decrease dimensionality in machine learning models".

Background: Machine learning (ML) prediction models in healthcare and pharmacy-related research face challenges with encoding high-dimensional Healthcare Coding Systems (HCSs) such as ICD, ATC, and DRG codes, given the trade-off between reducing model dimensionality and minimizing information loss.

Objectives: To investigate using Network Analysis modularity as a method to group HCSs to improve encoding in ML models.

Methods: The MIMIC-III dataset was utilized to create a multimorbidity network in which ICD-9 codes are the nodes and the edges are the number of patients sharing the same ICD-9 code pairs.

An introduction to network analysis for studies of medication use.

Background: Network Analysis (NA) is a method that has been used in various disciplines such as Social sciences and Ecology for decades. So far, NA has not been used extensively in studies of medication use. Only a handful of papers have used NA in Drug Prescription Networks (DPN).