The evolution of boosting algorithms

A Mayr, H Binder, O Gefeller… - Methods of information in …, 2014 - thieme-connect.com
Background: The concept of boosting emerged from the field of machine learning. The basic
idea is to boost the accuracy of a weak classifying tool by combining various instances into a …

Key use cases for artificial intelligence to reduce the frequency of adverse drug events: a scoping review

A Syrowatka, W Song, MG Amato, D Foer… - The Lancet Digital …, 2022 - thelancet.com
Adverse drug events (ADEs) represent one of the most prevalent types of health-care-
related harm, and there is substantial room for improvement in the way that they are …

Ensemble of machine learning algorithms using the stacked generalization approach to estimate the warfarin dose

Z Ma, P Wang, Z Gao, R Wang, K Khalighi - PloS one, 2018 - journals.plos.org
Warfarin dosing remains challenging due to narrow therapeutic index and highly individual
variability. Incorrect warfarin dosing is associated with devastating adverse events …

The value of artificial intelligence in laboratory medicine: current opinions and barriers to implementation

K Paranjape, M Schinkel, RD Hammer… - American Journal of …, 2021 - academic.oup.com
Objectives As laboratory medicine continues to undergo digitalization and automation,
clinical laboratorians will likely be confronted with the challenges associated with artificial …

[HTML][HTML] Machine learning in laboratory medicine: waiting for the flood?

F Cabitza, G Banfi - Clinical Chemistry and Laboratory Medicine …, 2018 - degruyter.com
This review focuses on machine learning and on how methods and models combining data
analytics and artificial intelligence have been applied to laboratory medicine so far. Although …

Comparison of nine statistical model based warfarin pharmacogenetic dosing algorithms using the racially diverse international warfarin pharmacogenetic consortium …

R Liu, X Li, W Zhang, HH Zhou - PloS one, 2015 - journals.plos.org
Objective Multiple linear regression (MLR) and machine learning techniques in
pharmacogenetic algorithm-based warfarin dosing have been reported. However …

[HTML][HTML] Machine learning in medication prescription: A systematic review

A Iancu, I Leb, HU Prokosch, W Rödle - International Journal of Medical …, 2023 - Elsevier
Background Medication prescription is a complex process that could benefit from current
research and development in machine learning through decision support systems …

Predicting the prolonged length of stay of general surgery patients: a supervised learning approach

MT Chuang, Y Hu, CL Lo - International Transactions in …, 2018 - Wiley Online Library
Determining the likelihood of a prolonged length of stay (LOS) for surgery patients can
improve medical resource management. This study was aimed at developing predictive …

Predicting the failure of dental implants using supervised learning techniques

CH Liu, CJ Lin, YH Hu, ZH You - Applied Sciences, 2018 - mdpi.com
Prosthodontic treatment has been a crucial part of dental treatment for patients with full
mouth rehabilitation. Dental implant surgeries that replace conventional dentures using …

Comparison of the predictive abilities of pharmacogenetics-based warfarin dosing algorithms using seven mathematical models in Chinese patients

X Li, R Liu, ZY Luo, H Yan, WH Huang, JY Yin… - …, 2015 - Taylor & Francis
Aim: This study is aimed to find the best predictive model for warfarin stable dosage.
Materials & methods: Seven models, namely multiple linear regression (MLR), artificial …