AIMC Topic: Middle Aged

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Enhancing weakly supervised data augmentation networks for thyroid nodule assessment using traditional and doppler ultrasound images.

Computers in biology and medicine
Thyroid ultrasound (US) is an essential tool for detecting and characterizing thyroid nodules. In this study, we propose an innovative approach to enhance thyroid nodule assessment by integrating Doppler US images with grayscale US images through wea...

Empowering heart attack treatment for women through machine learning and optimization techniques.

Computers in biology and medicine
Heart attack detection and treatment in women remain significantly under-optimized due to differences in symptom presentation and physiological characteristics compared to men, leading to delayed or incorrect diagnoses. Addressing this gap, this stud...

The implementation of computer-aided detection in an initial endoscopy training improves the quality measures of trainees' future colonoscopies: a retrospective cohort study.

Surgical endoscopy
INTRODUCTION: The implementation of computer-aided detection (CADe) systems has resulted in a growing number of young endoscopists being trained using AI-enhanced devices. The potential impact of AI-enhanced training on the trainees' future performan...

Landmark display system for laparoscopic inguinal hernia repair using artificial intelligence.

Surgical endoscopy
BACKGROUND: Chronic postoperative inguinal pain (CPIP) is a major complication of inguinal hernia repair and significantly affects patients' quality of life. Despite the widespread use of transabdominal preperitoneal repair (TAPP), CPIP still occurs....

Machine Learning-Based Prediction of Clinical Outcomes in Patients With Cancer Receiving Systemic Treatment Using Step Count Data Measured With Smartphones.

JCO clinical cancer informatics
PURPOSE: This study aimed to investigate whether changes in step count, measured using patients' own smartphones, could predict a clinical adverse event in the upcoming week in patients undergoing systemic anticancer treatments using machine learning...

Establishment of a machine learning-based predictive model with dual-center external validation: investigating the role of robotic surgery in preventing delayed gastric emptying for right-sided colon cancer.

Journal of robotic surgery
After colorectal surgery, delayed gastric emptying (DGE) is a clinically significant postoperative complication that significantly lowers patients' quality of life. The evolving application of robotic surgery in gastrointestinal oncology continues to...

AI-augmented differential diagnosis of granulomatous rosacea and lupus miliaris disseminatus faciei: A 23-year retrospective pilot study.

PloS one
Granulomatous rosacea (GR) and lupus miliaris disseminatus faciei (LMDF) exhibit overlapping clinical features, making their differentiation challenging. While histopathological examination remains the gold standard, it is invasive and time-consuming...

Improving a data mining based diagnostic support tool for rare diseases on the example of M. Fabry: Gender differences need to be taken into account.

PloS one
BACKGROUND: Rare diseases often present with a variety of clinical symptoms and therefore are challenging to diagnose. Fabry disease is an x-linked rare metabolic disorder. The severity of symptoms is usually different in men and women. Since therape...

Deep Learning-Based Automated Detection of the Middle Cerebral Artery in Transcranial Doppler Ultrasound Examinations.

Ultrasound in medicine & biology
OBJECTIVE: Transcranial Doppler (TCD) ultrasound has significant clinical value for assessing cerebral hemodynamics, but its reliance on operator expertise limits broader clinical adoption. In this work, we present a lightweight real-time deep learni...