AIMC Topic: Female

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Mental state classification based on electroencephalogram (EEG) using multiclass support vector machine.

The Medical journal of Malaysia
INTRODUCTION: Mental state refers to a person's state of mind from various perspectives, including consciousness, intention, and functionalism. Mental states closely related to everyday life include the concentrating state, neutral state, and relaxat...

Using Artificial Intelligence for an Efficient Prediction of Outcomes of Deep Anterior Lamellar Keratoplasty (DALK) in Advanced Keratoconus.

Translational vision science & technology
PURPOSE: To identify and analyze clinical risk factors and imaging parameters influencing the outcomes of deep anterior lamellar keratoplasty (DALK) for advanced keratoconus (KC) using an artificial intelligence (AI) model.

Novel Artificial Intelligence-Based Quantification of Anterior Chamber Inflammation Using Vision Transformers.

Translational vision science & technology
PURPOSE: Quantitative assessment of inflammation is critical for the accurate diagnosis and effective management of uveitis. This study aims to introduce a novel three-dimensional vision transformer approach using anterior segment optical coherence t...

Image-Based Deep Learning Model for Predicting Lymph Node Metastasis in Lung Adenocarcinoma With CT ≤ 2 cm.

Thoracic cancer
BACKGROUND: Lymph node metastasis (LNM) poses a considerable threat to survival in lung adenocarcinoma. Currently, minor resection is the recommended surgical approach for small-diameter lung cancer. The accurate preoperative identification of LNM in...

Identifying GAP43, NMU, and TEX29 as Potential Prognostic Biomarkers for COPD Combined With Lung Cancer Patients Using Machine Learning.

The journal of gene medicine
Chronic obstructive pulmonary disease (COPD) and lung cancer, frequently comorbid conditions intricately linked through smoking, represent significant global health challenges. COPD is a common comorbidity in nonsmall cell lung cancer (NSCLC) patient...

Generative AI mitigates representation bias and improves model fairness through synthetic health data.

PLoS computational biology
Representation bias in health data can lead to unfair decisions and compromise the generalisability of research findings. As a consequence, underrepresented subpopulations, such as those from specific ethnic backgrounds or genders, do not benefit equ...

Investigating the Link between Type 2 Diabetes and Epstein-Barr Virus: a Machine Learning and Mendelian Randomization.

Clinical laboratory
BACKGROUND: Epstein-Barr virus (EBV) is a ubiquitous herpesvirus that is known to cause infectious mononucleosis and is associated with several autoimmune diseases and cancers through immune system dysregulation and chronic inflammatory mechanisms.

[Usage of artificial intelligence in the clinical practice of urologists in observations with renal parenchymal neoplasms].

Urologiia (Moscow, Russia : 1999)
OBJECTIVE: to assess the needs and attitudes of urologists regarding the use of technologies related to artificial intelligence, particularly the web platform "Sechenov.AI_nephro", in the surgical treatment of patients with renal parenchymal neoplasm...

Deep Learning Study of Alkaptonuria Spinal Disease Assesses Global and Regional Severity and Detects Occult Treatment Status.

Journal of inherited metabolic disease
Deep learning (DL) is increasingly used to analyze medical imaging, but is less refined for rare conditions, which require novel pre-processing and analytical approaches. To assess DL in the context of rare diseases, this study focused on alkaptonuri...