AIMC Topic: Humans

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Estimating Visual Acuity With Spectacle Correction From Fundus Photos Using Artificial Intelligence.

JAMA network open
IMPORTANCE: Determining spectacle-corrected visual acuity (VA) is essential when managing many ophthalmic diseases. If artificial intelligence (AI) evaluations of macular images estimated this VA from a fundus image, AI might provide spectacle-correc...

Non-invasive blood glucose monitoring using PPG signals with various deep learning models and implementation using TinyML.

Scientific reports
Accurate and continuous blood glucose monitoring is essential for effective diabetes management, yet traditional finger pricking methods are often inconvenient and painful. To address this issue, photoplethysmography (PPG) presents a promising non-in...

Noninvasive diagnosis of significant liver fibrosis in patients with chronic hepatitis B using nomogram and machine learning models.

Scientific reports
This study aims to construct and validate noninvasive diagnosis models for evaluating significant liver fibrosis in patients with chronic hepatitis B (CHB). A cohort of 259 CHB patients were selected as research subjects. Through random grouping, 182...

Deciphering the cellular and molecular landscape of pulmonary fibrosis through single-cell sequencing and machine learning.

Journal of translational medicine
Pulmonary fibrosis is characterized by progressive lung scarring, leading to a decline in lung function and an increase in morbidity and mortality. This study leverages single-cell sequencing and machine learning to unravel the complex cellular and m...

Influence of next-generation artificial intelligence on headache research, diagnosis and treatment: the junior editorial board members' vision - part 2.

The journal of headache and pain
Part 2 explores the transformative potential of artificial intelligence (AI) in addressing the complexities of headache disorders through innovative approaches, including digital twin models, wearable healthcare technologies and biosensors, and AI-dr...

Predicting autoimmune thyroiditis in primary Sjogren's syndrome patients using a random forest classifier: a retrospective study.

Arthritis research & therapy
BACKGROUND: Primary Sjogren's syndrome (pSS) and autoimmune thyroiditis (AIT) share overlapping genetic and immunological profiles. This retrospective study evaluates the efficacy of machine learning algorithms, with a focus on the Random Forest Clas...

Logical reasoning for human activity recognition based on multisource data from wearable device.

Scientific reports
Smart wearable devices detection and recording of people's everyday activities is critical for health monitoring, helping persons with disabilities, and providing care for the elderly. Most of the research that is being conducted uses a machine learn...

Weakly supervised deep learning-based classification for histopathology of gliomas: a single center experience.

Scientific reports
Multiple artificial intelligence systems have been created to facilitate accurate and prompt histopathological diagnosis of tumors using hematoxylin-eosin-stained slides. We aimed to investigate whether weakly supervised deep learning can aid in glio...

Enhancing the performance of SSVEP-based BCIs by combining task-related component analysis and deep neural network.

Scientific reports
Steady-State Visually Evoked Potential (SSVEP) signals can be decoded by either a traditional machine learning algorithm or a deep learning network. Combining the two methods is expected to enhance the performance of an SSVEP-based brain-computer int...