AIMC Topic: Humans

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Application of Artificial Intelligence in Community-Based Primary Health Care: Systematic Scoping Review and Critical Appraisal.

Journal of medical Internet research
BACKGROUND: Research on the integration of artificial intelligence (AI) into community-based primary health care (CBPHC) has highlighted several advantages and disadvantages in practice regarding, for example, facilitating diagnosis and disease manag...

Ophthalmic Disease Detection via Deep Learning With a Novel Mixture Loss Function.

IEEE journal of biomedical and health informatics
With the popularization of computer-aided diagnosis (CAD) technologies, more and more deep learning methods are developed to facilitate the detection of ophthalmic diseases. In this article, the deep learning-based detections for some common eye dise...

Method of Tumor Pathological Micronecrosis Quantification Via Deep Learning From Label Fuzzy Proportions.

IEEE journal of biomedical and health informatics
The presence of necrosis is associated with tumor progression and patient outcomes in many cancers, but existing analyses rarely adopt quantitative methods because the manual quantification of histopathological features is too expensive. We aim to ac...

Accurate and Feasible Deep Learning Based Semi-Automatic Segmentation in CT for Radiomics Analysis in Pancreatic Neuroendocrine Neoplasms.

IEEE journal of biomedical and health informatics
Current clinical practice or radiomics studies of pancreatic neuroendocrine neoplasms (pNENs) require manual delineation of the lesions in computed tomography (CT) images, which is time-consuming and subjective. We used a semi-automatic deep learning...

A Combinatorial Deep Learning Structure for Precise Depth of Anesthesia Estimation From EEG Signals.

IEEE journal of biomedical and health informatics
Electroencephalography (EEG) is commonly used to measure the depth of anesthesia (DOA) because EEG reflects surgical pain and state of the brain. However, precise and real-time estimation of DOA index for painful surgical operations is challenging du...

Machine Learning for Real-Time Heart Disease Prediction.

IEEE journal of biomedical and health informatics
Heart-related anomalies are among the most common causes of death worldwide. Patients are often asymptomatic until a fatal event happens, and even when they are under observation, trained personnel is needed in order to identify a heart anomaly. In t...

A Deep Learning Approach to Predict Diabetes' Cardiovascular Complications From Administrative Claims.

IEEE journal of biomedical and health informatics
People with diabetes require lifelong access to healthcare services to delay the onset of complications. Their disease management processes generate great volumes of data across several domains, from clinical to administrative. Difficulties in access...

Limitations of Transformers on Clinical Text Classification.

IEEE journal of biomedical and health informatics
Bidirectional Encoder Representations from Transformers (BERT) and BERT-based approaches are the current state-of-the-art in many natural language processing (NLP) tasks; however, their application to document classification on long clinical texts is...

An Attention-Based Mechanism to Combine Images and Metadata in Deep Learning Models Applied to Skin Cancer Classification.

IEEE journal of biomedical and health informatics
Computer-aided skin cancer classification systems built with deep neural networks usually yield predictions based only on images of skin lesions. Despite presenting promising results, it is possible to achieve higher performance by taking into accoun...

Learning a Deep CNN Denoising Approach Using Anatomical Prior Information Implemented With Attention Mechanism for Low-Dose CT Imaging on Clinical Patient Data From Multiple Anatomical Sites.

IEEE journal of biomedical and health informatics
Dose reduction in computed tomography (CT) has gained considerable attention in clinical applications because it decreases radiation risks. However, a lower dose generates noise in low-dose computed tomography (LDCT) images. Previous deep learning (D...