AIMC Topic: Humans

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Challenges to implementing artificial intelligence in healthcare: a qualitative interview study with healthcare leaders in Sweden.

BMC health services research
BACKGROUND: Artificial intelligence (AI) for healthcare presents potential solutions to some of the challenges faced by health systems around the world. However, it is well established in implementation and innovation research that novel technologies...

Automated image curation in diabetic retinopathy screening using deep learning.

Scientific reports
Diabetic retinopathy (DR) screening images are heterogeneous and contain undesirable non-retinal, incorrect field and ungradable samples which require curation, a laborious task to perform manually. We developed and validated single and multi-output ...

How physical techniques improve the transdermal permeation of therapeutics: A review.

Medicine
BACKGROUND: Transdermal delivery is very important in pharmaceutics. However, the barrier function of the stratum corneum hinders drugs absorption. How to improve transdermal delivery efficiency is a hot topic. The key advantages of physical technolo...

Improving Breast Tumor Segmentation in PET via Attentive Transformation Based Normalization.

IEEE journal of biomedical and health informatics
Positron Emission Tomography (PET) has become a preferred imaging modality for cancer diagnosis, radiotherapy planning, and treatment responses monitoring. Accurate and automatic tumor segmentation is the fundamental requirement for these clinical ap...

RAVIR: A Dataset and Methodology for the Semantic Segmentation and Quantitative Analysis of Retinal Arteries and Veins in Infrared Reflectance Imaging.

IEEE journal of biomedical and health informatics
The retinal vasculature provides important clues in the diagnosis and monitoring of systemic diseases including hypertension and diabetes. The microvascular system is of primary involvement in such conditions, and the retina is the only anatomical si...

Handling Imbalanced Data: Uncertainty-Guided Virtual Adversarial Training With Batch Nuclear-Norm Optimization for Semi-Supervised Medical Image Classification.

IEEE journal of biomedical and health informatics
In manyclinical settings, a lot of medical image datasets suffer from imbalance problems, which makes predictions of trained models to be biased toward majority classes. Semi-supervised Learning (SSL) algorithms trained with such imbalanced datasets ...

All-Around Real Label Supervision: Cyclic Prototype Consistency Learning for Semi-Supervised Medical Image Segmentation.

IEEE journal of biomedical and health informatics
Semi-supervised learning has substantially advanced medical image segmentation since it alleviates the heavy burden of acquiring the costly expert-examined annotations. Especially, the consistency-based approaches have attracted more attention for th...

A Deep Learning Approach for Detecting Otitis Media From Wideband Tympanometry Measurements.

IEEE journal of biomedical and health informatics
OBJECTIVE: In this study, wepropose an automatic diagnostic algorithm for detecting otitis media based on wideband tympanometry measurements.

A Multimodal AI System for Out-of-Distribution Generalization of Seizure Identification.

IEEE journal of biomedical and health informatics
Artificial intelligence (AI) and health sensory data-fusion hold the potential to automate many laborious and time-consuming processes in hospitals or ambulatory settings, e.g. home monitoring and telehealth. One such unmet challenge is rapid and acc...

Privacy-Preserving Multi-Class Support Vector Machine Model on Medical Diagnosis.

IEEE journal of biomedical and health informatics
With the rapid development of machine learning in the medical cloud system, cloud-assisted medical computing provides a concrete platform for remote rapid medical diagnosis services. Support vector machine (SVM), as one of the important algorithms of...