AIMC Topic: Aged
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Landmark display system for laparoscopic inguinal hernia repair using artificial intelligence.
Surgical endoscopy
Jun 30, 2025
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
Jun 30, 2025
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
Jun 30, 2025
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
Jun 30, 2025
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...
Interpretable machine learning for predicting isolated basal septal hypertrophy.
PloS one
Jun 30, 2025
BACKGROUND: The basal septal hypertrophy(BSH) is an often under-recognized morphological change in the left ventricle. This is a common echocardiographic finding with a prevalence of approximately 7-20%, which may indicate early structural and functi...
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
Jun 30, 2025
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 models for predicting hearing thresholds based on joint stimulus-frequency otoacoustic emissions and distortion-product otoacoustic emissions.
Hearing research
Jun 29, 2025
According to the dual-source generation hypothesis, stimulus-frequency otoacoustic emissions (SFOAEs) and distortion-product OAEs (DPOAEs) arise from different cochlear mechanisms, and both are capable of characterizing hearing loss. However, their j...
Predictive Value of Tests
Signal Processing, Computer-Assisted
Acoustic Stimulation
Audiometry, Pure-Tone
Middle Aged
Case-Control Studies
Deep Learning
Adolescent
Hearing Loss, Sensorineural
Hearing
Auditory Threshold
Cochlea
Otoacoustic Emissions, Spontaneous
Humans
Neural Networks, Computer
Female
Young Adult
Adult
Male
Reproducibility of Results
Aged
Comparative analysis of machine learning-derived nomogram and biomarkers in predicting side-specific extraprostatic extension: Preliminary findings.
Clinical imaging
Jun 28, 2025
AIM: This study aimed to assess and compare the performance of nomograms and machine learning (ML) techniques using preoperative biomarkers for predicting side-specific extraprostatic extension (EPE) in prostate cancer, which is linked to poor outcom...
Evaluation of meibomian gland dysfunction with deep learning model considering different datasets and gland morphology.
Computers in biology and medicine
Jun 28, 2025
Meibomian gland dysfunction (MGD) is recognized as the primary cause of evaporative-type dry eye disease (DED). Diagnosis typically involves assessing meibomian gland (MG) morphology alongside symptom evaluation. Traditionally, experts manually grade...
Classification of knee osteoarthritis severity using markerless motion capture and long short-term memory fully convolutional network.
Computers in biology and medicine
Jun 28, 2025
This study explored the integration of markerless motion capture and deep learning to classify knee osteoarthritis severity based on gait kinematics, providing an alternative to traditional assessment methods. We employed a Long Short-Term Memory Ful...
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