AIMC Topic: Humans

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AI-based Strategies to Reduce Workload in Breast Cancer Screening with Mammography and Tomosynthesis: A Retrospective Evaluation.

Radiology
Background The workflow of breast cancer screening programs could be improved given the high workload and the high number of false-positive and false-negative assessments. Purpose To evaluate if using an artificial intelligence (AI) system could redu...

Effect of AI Explanations on Human Perceptions of Patient-Facing AI-Powered Healthcare Systems.

Journal of medical systems
Ongoing research efforts have been examining how to utilize artificial intelligence technology to help healthcare consumers make sense of their clinical data, such as diagnostic radiology reports. How to promote the acceptance of such novel technolog...

Machine learning-based mortality prediction model for heat-related illness.

Scientific reports
In this study, we aimed to develop and validate a machine learning-based mortality prediction model for hospitalized heat-related illness patients. After 2393 hospitalized patients were extracted from a multicentered heat-related illness registry in ...

Machine learning based models for prediction of subtype diagnosis of primary aldosteronism using blood test.

Scientific reports
Primary aldosteronism (PA) is associated with an increased risk of cardiometabolic diseases, especially in unilateral subtype. Despite its high prevalence, the case detection rate of PA is limited, partly because of no clinical models available in ge...

Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning.

BMC endocrine disorders
INTRODUCTION: Recent studies have reported that HbA1c and lipid variability is useful for risk stratification in diabetes mellitus. The present study evaluated the predictive value of the baseline, subsequent mean of at least three measurements and v...

Collecting specialty-related medical terms: Development and evaluation of a resource for Spanish.

BMC medical informatics and decision making
BACKGROUND: Controlled vocabularies are fundamental resources for information extraction from clinical texts using natural language processing (NLP). Standard language resources available in the healthcare domain such as the UMLS metathesaurus or SNO...

Machine Learning and Natural Language Processing in Mental Health: Systematic Review.

Journal of medical Internet research
BACKGROUND: Machine learning systems are part of the field of artificial intelligence that automatically learn models from data to make better decisions. Natural language processing (NLP), by using corpora and learning approaches, provides good perfo...

Projecting COVID-19 disease severity in cancer patients using purposefully-designed machine learning.

BMC infectious diseases
BACKGROUND: Accurately predicting outcomes for cancer patients with COVID-19 has been clinically challenging. Numerous clinical variables have been retrospectively associated with disease severity, but the predictive value of these variables, and how...

Ensuring that biomedical AI benefits diverse populations.

EBioMedicine
Artificial Intelligence (AI) can potentially impact many aspects of human health, from basic research discovery to individual health assessment. It is critical that these advances in technology broadly benefit diverse populations from around the worl...

Efficient Automated Disease Diagnosis Using Machine Learning Models.

Journal of healthcare engineering
Recently, many researchers have designed various automated diagnosis models using various supervised learning models. An early diagnosis of disease may control the death rate due to these diseases. In this paper, an efficient automated disease diagno...