AIMC Topic: Humans

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DCDLN: A densely connected convolutional dynamic learning network for malaria disease diagnosis.

Neural networks : the official journal of the International Neural Network Society
Malaria is a significant health concern worldwide, particularly in Africa where its prevalence is still alarmingly high. Using artificial intelligence algorithms to diagnose cells with malaria provides great convenience for clinicians. In this paper,...

Data-driven shortened Insomnia Severity Index (ISI): a machine learning approach.

Sleep & breathing = Schlaf & Atmung
BACKGROUND: The Insomnia Severity Index (ISI) is a widely used questionnaire with seven items for identifying the risk of insomnia disorder. Although the ISI is still short, more shortened versions are emerging for repeated monitoring in routine clin...

Identification and Connectomic Profiling of Concussion Using Bayesian Machine Learning.

Journal of neurotrauma
Accurate early diagnosis of concussion is useful to prevent sequelae and improve neurocognitive outcomes. Early after head impact, concussion diagnosis may be doubtful in persons whose neurological, neuroradiological, and/or neurocognitive examinatio...

Machine learning model for predicting stroke recurrence in adult stroke patients with moyamoya disease and factors of stroke recurrence.

Clinical neurology and neurosurgery
OBJECT: The aim of this study was at building an effective machine learning model to contribute to the prediction of stroke recurrence in adult stroke patients subjected to moyamoya disease (MMD), while at analyzing the factors for stroke recurrence.

Motion correction and super-resolution for multi-slice cardiac magnetic resonance imaging via an end-to-end deep learning approach.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Accurate reconstruction of a high-resolution 3D volume of the heart is critical for comprehensive cardiac assessments. However, cardiac magnetic resonance (CMR) data is usually acquired as a stack of 2D short-axis (SAX) slices, which suffers from the...

Performance of ChatGPT in Answering Clinical Questions on the Practical Guideline of Blepharoptosis.

Aesthetic plastic surgery
BACKGROUND: ChatGPT is a free artificial intelligence (AI) language model developed and released by OpenAI in late 2022. This study aimed to evaluate the performance of ChatGPT to accurately answer clinical questions (CQs) on the Guideline for the Ma...

A deep learning-based 3D Prompt-nnUnet model for automatic segmentation in brachytherapy of postoperative endometrial carcinoma.

Journal of applied clinical medical physics
PURPOSE: To create and evaluate a three-dimensional (3D) Prompt-nnUnet module that utilizes the prompts-based model combined with 3D nnUnet for producing the rapid and consistent autosegmentation of high-risk clinical target volume (HR CTV) and organ...

Predicting Blood Glucose Levels with Organic Neuromorphic Micro-Networks.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Accurate glucose prediction is vital for diabetes management. Artificial intelligence and artificial neural networks (ANNs) are showing promising results for reliable glucose predictions, offering timely warnings for glucose fluctuations. The transla...

Expert-level sleep staging using an electrocardiography-only feed-forward neural network.

Computers in biology and medicine
Reliable classification of sleep stages is crucial in sleep medicine and neuroscience research for providing valuable insights, diagnoses, and understanding of brain states. The current gold standard method for sleep stage classification is polysomno...