AIMC Topic: Humans

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Deep learning-based spectroscopic single-molecule localization microscopy.

Journal of biomedical optics
SIGNIFICANCE: Spectroscopic single-molecule localization microscopy (sSMLM) takes advantage of nanoscopy and spectroscopy, enabling sub-10 nm resolution as well as simultaneous multicolor imaging of multi-labeled samples. Reconstruction of raw sSMLM ...

Investigation of the usefulness of a bile duct biopsy and bile cytology using a hyperspectral camera and machine learning.

Pathology international
To improve the efficiency of pathological diagnoses, the development of automatic pathological diagnostic systems using artificial intelligence (AI) is progressing; however, problems include the low interpretability of AI technology and the need for ...

Early diagnosis of persons with von Willebrand disease using a machine learning algorithm and real-world data.

Expert review of hematology
BACKGROUND: Von Willebrand disease (VWD) is underdiagnosed, often delaying treatment. VWD claims coding is limited and includes no severity qualifiers; improved identification methods for VWD are needed. The aim of this study is to identify and chara...

Position-Aware Indoor Human Activity Recognition Using Multisensors Embedded in Smartphones.

Sensors (Basel, Switzerland)
Composite indoor human activity recognition is very important in elderly health monitoring and is more difficult than identifying individual human movements. This article proposes a sensor-based human indoor activity recognition method that integrate...

Quantifying Nocturnal Scratch in Atopic Dermatitis: A Machine Learning Approach Using Digital Wrist Actigraphy.

Sensors (Basel, Switzerland)
Nocturnal scratching substantially impairs the quality of life in individuals with skin conditions such as atopic dermatitis (AD). Current clinical measurements of scratch rely on patient-reported outcomes (PROs) on itch over the last 24 h. Such meas...

Detection Method of Epileptic Seizures Using a Neural Network Model Based on Multimodal Dual-Stream Networks.

Sensors (Basel, Switzerland)
Epilepsy is a common neurological disorder, and its diagnosis mainly relies on the analysis of electroencephalogram (EEG) signals. However, the raw EEG signals contain limited recognizable features, and in order to increase the recognizable features ...

Evidence-Based Learning Strategies in Medicine Using AI.

JMIR medical education
Large language models (LLMs), like ChatGPT, are transforming the landscape of medical education. They offer a vast range of applications, such as tutoring (personalized learning), patient simulation, generation of examination questions, and streamlin...

Natural language processing to identify and characterize spondyloarthritis in clinical practice.

RMD open
OBJECTIVE: This study aims to use a novel technology based on natural language processing (NLP) to extract clinical information from electronic health records (EHRs) to characterise the clinical profile of patients diagnosed with spondyloarthritis (S...

Deep learning of mammogram images to reduce unnecessary breast biopsies: a preliminary study.

Breast cancer research : BCR
BACKGROUND: Patients with a Breast Imaging Reporting and Data System (BI-RADS) 4 mammogram are currently recommended for biopsy. However, 70-80% of the biopsies are negative/benign. In this study, we developed a deep learning classification algorithm...

Real-time sports injury monitoring system based on the deep learning algorithm.

BMC medical imaging
In response to the low real-time performance and accuracy of traditional sports injury monitoring, this article conducts research on a real-time injury monitoring system using the SVM model as an example. Video detection is performed to capture human...