AIMC Topic: Adult

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Artificial intelligence-based classification of cardiac autonomic neuropathy from retinal fundus images in patients with diabetes: The Silesia Diabetes Heart Study.

Cardiovascular diabetology
BACKGROUND: Cardiac autonomic neuropathy (CAN) in diabetes mellitus (DM) is independently associated with cardiovascular (CV) events and CV death. Diagnosis of this complication of DM is time-consuming and not routinely performed in the clinical prac...

Machine Learning and Clinical Predictors of Mortality in Cardiac Arrest Patients: A Comprehensive Analysis.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND Cardiac arrest (CA) is a global public health challenge. This study explored the predictors of mortality and their interactions utilizing machine learning algorithms and their related mortality odds among patients following CA. MATERIAL AN...

Attitude of aspiring orthopaedic surgeons towards artificial intelligence: a multinational cross-sectional survey study.

Archives of orthopaedic and trauma surgery
INTRODUCTION: The purpose of this study was to evaluate the perspectives of aspiring orthopaedic surgeons on artificial intelligence (AI), analysing how gender, AI knowledge, and technical inclination influence views on AI. Additionally, the extent t...

Prognostic enrichment for early-stage Huntington's disease: An explainable machine learning approach for clinical trial.

NeuroImage. Clinical
BACKGROUND: In Huntington's disease clinical trials, recruitment and stratification approaches primarily rely on genetic load, cognitive and motor assessment scores. They focus less on in vivo brain imaging markers, which reflect neuropathology well ...

Predictability of varicocele repair success: preliminary results of a machine learning-based approach.

Asian journal of andrology
Varicocele is a prevalent condition in the infertile male population. However, to date, which patients may benefit most from varicocele repair is still a matter of debate. The purpose of this study was to evaluate whether certain preintervention sper...

Multilevel hybrid handcrafted feature extraction based depression recognition method using speech.

Journal of affective disorders
BACKGROUND AND PURPOSE: Diagnosis of depression is based on tests performed by psychiatrists and information provided by patients or their relatives. In the field of machine learning (ML), numerous models have been devised to detect depression automa...

Deep learning versus manual morphology-based embryo selection in IVF: a randomized, double-blind noninferiority trial.

Nature medicine
To assess the value of deep learning in selecting the optimal embryo for in vitro fertilization, a multicenter, randomized, double-blind, noninferiority parallel-group trial was conducted across 14 in vitro fertilization clinics in Australia and Euro...

A deep learning approach to identify the fetal head position using transperineal ultrasound during labor.

European journal of obstetrics, gynecology, and reproductive biology
OBJECTIVES: To develop a deep learning (DL)-model using convolutional neural networks (CNN) to automatically identify the fetal head position at transperineal ultrasound in the second stage of labor.

Non-invasive prediction of axillary lymph node dissection exemption in breast cancer patients post-neoadjuvant therapy: A radiomics and deep learning analysis on longitudinal DCE-MRI data.

Breast (Edinburgh, Scotland)
PURPOSE: In breast cancer (BC) patients with clinical axillary lymph node metastasis (cN+) undergoing neoadjuvant therapy (NAT), precise axillary lymph node (ALN) assessment dictates therapeutic strategy. There is a critical demand for a precise meth...

Machine learning approaches to predict whether MEPs can be elicited via TMS.

Journal of neuroscience methods
BACKGROUND: Transcranial magnetic stimulation (TMS) is a valuable technique for assessing the function of the motor cortex and cortico-muscular pathways. TMS activates the motoneurons in the cortex, which after transmission along cortico-muscular pat...