AIMC Topic: Machine Learning

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An approachable, flexible and practical machine learning workshop for biologists.

Bioinformatics (Oxford, England)
SUMMARY: The increasing prevalence and importance of machine learning in biological research have created a need for machine learning training resources tailored towards biological researchers. However, existing resources are often inaccessible, infe...

Gender classification in classical fiction: A computational analysis of 1113 fictions.

Mathematical biosciences and engineering : MBE
Recent decades have witnessed the rapid development of literary studies on gender and writing style. One of the common limitations of previous studies is that they analyze only a few texts, which some researchers have already pointed out. In this stu...

Use of unstructured text in prognostic clinical prediction models: a systematic review.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: This systematic review aims to assess how information from unstructured text is used to develop and validate clinical prognostic prediction models. We summarize the prediction problems and methodological landscape and determine whether usi...

Assessing socioeconomic bias in machine learning algorithms in health care: a case study of the HOUSES index.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Artificial intelligence (AI) models may propagate harmful biases in performance and hence negatively affect the underserved. We aimed to assess the degree to which data quality of electronic health records (EHRs) affected by inequities rel...

Artificial Intelligence-based Radiomics in the Era of Immuno-oncology.

The oncologist
The recent, rapid advances in immuno-oncology have revolutionized cancer treatment and spurred further research into tumor biology. Yet, cancer patients respond variably to immunotherapy despite mounting evidence to support its efficacy. Current meth...

Predicting Readmission Following Hospital Treatment for Patients with Alcohol Related Diagnoses in an Australian Regional Health District.

Studies in health technology and informatics
This study aims to investigate the prediction of hospital readmission of alcohol use disorder patients within 28 days of discharge and compare the performance of six machine learning methods i.e., random forest (RF), logistics regression, linear supp...

Comparing Multiple Models for Section Header Classification with Feature Evaluation.

Studies in health technology and informatics
We present on the performance evaluation of machine learning (ML) and Natural Language Processing (NLP) based Section Header classification. The section headers classification task was performed as a two-pass system. The first pass detects a section ...

Characterizing Infant Mortality Using Data Mining - A Case Study in Two Brazilian States - Santa Catarina and Amapá.

Studies in health technology and informatics
Infant mortality is characterized by the death of young children under the age of one, and it is an issue affecting millions of children in the world. The objective of this article is to employ concepts of knowledge discovery in databases, specifical...

Accuracies of Training Labels and Machine Learning Models: Experiments on Delirium and Simulated Data.

Studies in health technology and informatics
Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the lab...

Using Data-Driven Machine Learning to Predict Unplanned ICU Transfers with Critical Deterioration from Electronic Health Records.

Studies in health technology and informatics
OBJECTIVE: We aimed to develop a data-driven machine learning model for predicting critical deterioration events from routinely collected EHR data in hospitalized children.