AIMC Topic: Humans

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An effective flowchart for multimodal brain tumor binary classification with ranked 3D texture features.

Scientific reports
Brain tumors have complex structures, and their shape, density, and size can vary widely. Consequently, their accurate classification, which involves identifying features that best describe the tumor data, is challenging. Using classical 2D texture f...

A development of machine learning models to preoperatively predict insufficient clinical improvement after total knee arthroplasty.

Journal of orthopaedic surgery and research
BACKGROUND: Identifying patients unlikely to achieve meaningful improvement following total knee arthroplasty (TKA) supports more effective shared decision-making (SDM). This study aimed to develop and validate machine learning (ML) models that preop...

Investigating potential biomarkers associated with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis using Mendelian randomization and transcriptomic analysis.

Arthritis research & therapy
BACKGROUND: Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is an autoimmune disorder characterized by multi-organ involvement. Early identification and accurate diagnosis of AAV is crucial for improving prognosis. However, res...

Stacking ensemble learning models diagnose pulmonary infections using host transcriptome data from metatranscriptomics.

Scientific reports
The prompt diagnosis of pulmonary infections with unknown etiology in patients in severe condition remains a challenge due to the lack of rapid and effective diagnostic methods. While metatranscriptomic sequencing offers a powerful approach, its clin...

Visual language transformer framework for multimodal dance performance evaluation and progression monitoring.

Scientific reports
Dance is often perceived as complex due to the need for coordinating multiple body movements and precisely aligning them with musical rhythm and content. Research in automatic dance performance assessment has the potential to enhance individuals' sen...

Determination of miRNA in tear extracellular vesicles significantly associated with treatment-requiring retinopathy of prematurity: a pilot study.

Scientific reports
Retinopathy of prematurity (ROP) develops in some premature infants and may be characterized by permanent severe retinal damage necessitating early detection and prompt treatment. The purpose of this study was to investigate whether specific miRNAs i...

Unsupervised clustering of biochemical markers reveals health profiles associated with function and survival in active aging.

Scientific reports
This study explores the relationships between biochemical phenotypes identified using machine learning, and key health outcomes, including body composition, physical function, and mortality risk. Data were collected from 536 physically active Spanish...

Enhancing frozen histological section images using permanent-section-guided deep learning with nuclei attention.

Scientific reports
In histological pathology, frozen sections are often used for rapid diagnosis during surgeries, as they can be produced within minutes. However, they suffer from artifacts and often lack crucial diagnostic details, particularly within the cell nuclei...

A study on the effectiveness of machine learning models for hepatitis prediction.

Scientific reports
Hepatitis continues to be a major global health challenge, leading to high morbidity and mortality rates. Despite advances in diagnosis and treatment, early prediction of hepatitis outcomes remains an essential area for improvement. This study seeks ...

Entropy-based risk network identification in adolescent self-injurious behavior using machine learning and network analysis.

Translational psychiatry
Adolescent Self-Injurious Behavior (SIB) is a significant global public health issue, with a lifetime prevalence rate of approximately 13.7%. As awareness of SIB rises, there is an urgent need for effective prediction mechanisms to enable early ident...