AIMC Topic: Humans

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Fast screening of covariates in population models empowered by machine learning.

Journal of pharmacokinetics and pharmacodynamics
One of the objectives of Pharmacometry (PMX) population modeling is the identification of significant and clinically relevant relationships between parameters and covariates. Here, we demonstrate how this complex selection task could benefit from sup...

An interpretable machine learning prognostic system for locoregionally advanced nasopharyngeal carcinoma based on tumor burden features.

Oral oncology
OBJECTIVES: We aimed to build a survival system by combining a highly-accurate machine learning (ML) model with explainable artificial intelligence (AI) techniques to predict distant metastasis in locoregionally advanced nasopharyngeal carcinoma (NPC...

Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning.

IEEE transactions on bio-medical engineering
BACKGROUND: Despite recent significant progress in the development of automatic sleep staging methods, building a good model still remains a big challenge for sleep studies with a small cohort due to the data-variability and data-inefficiency issues....

Development of a Wearable Camera and AI Algorithm for Medication Behavior Recognition.

Sensors (Basel, Switzerland)
As many as 40% to 50% of patients do not adhere to long-term medications for managing chronic conditions, such as diabetes or hypertension. Limited opportunity for medication monitoring is a major problem from the perspective of health professionals....

Identifying Images of Dead Chickens with a Chicken Removal System Integrated with a Deep Learning Algorithm.

Sensors (Basel, Switzerland)
The chicken industry, in which broiler chickens are bred, is the largest poultry industry in Taiwan. In a traditional poultry house, breeders must usually observe the health of the broilers in person on the basis of their breeding experience at regul...

Spectroscopic and deep learning-based approaches to identify and quantify cerebral microhemorrhages.

Scientific reports
Cerebral microhemorrhages (CMHs) are associated with cerebrovascular disease, cognitive impairment, and normal aging. One method to study CMHs is to analyze histological sections (5-40 μm) stained with Prussian blue. Currently, users manually and sub...

Permutation-based identification of important biomarkers for complex diseases via machine learning models.

Nature communications
Study of human disease remains challenging due to convoluted disease etiologies and complex molecular mechanisms at genetic, genomic, and proteomic levels. Many machine learning-based methods have been developed and widely used to alleviate some anal...

Generalisability through local validation: overcoming barriers due to data disparity in healthcare.

BMC ophthalmology
Cho et al. report deep learning model accuracy for tilted myopic disc detection in a South Korean population. Here we explore the importance of generalisability of machine learning (ML) in healthcare, and we emphasise that recurrent underrepresentati...

A Review of Applications of Machine Learning in Mammography and Future Challenges.

Oncology
BACKGROUND: The aim of this study is to systematically review the literature to summarize the evidence surrounding the clinical utility of artificial intelligence (AI) in the field of mammography. Databases from PubMed, IEEE Xplore, and Scopus were s...