AIMC Topic: Humans

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Within-Session Reliability of fNIRS in Robot-Assisted Upper-Limb Training.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Functional near-infrared spectroscopy (fNIRS) seems opportune for neurofeedback in robot-assisted rehabilitation training due to its noninvasive, less physical restriction, and no electromagnetic disturbance. Previous research has proved the cross-se...

Preoperative detection of hepatocellular carcinoma's microvascular invasion on CT-scan by machine learning and radiomics: A preliminary analysis.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
INTRODUCTION: Microvascular invasion (MVI) is the main risk factor for overall mortality and recurrence after surgery for hepatocellular carcinoma (HCC).The aim was to train machine-learning models to predict MVI on preoperative CT scan.

A review of self-supervised, generative, and few-shot deep learning methods for data-limited magnetic resonance imaging segmentation.

NMR in biomedicine
Magnetic resonance imaging (MRI) is a ubiquitous medical imaging technology with applications in disease diagnostics, intervention, and treatment planning. Accurate MRI segmentation is critical for diagnosing abnormalities, monitoring diseases, and d...

Harnessing artificial intelligence in bariatric surgery: comparative analysis of ChatGPT-4, Bing, and Bard in generating clinician-level bariatric surgery recommendations.

Surgery for obesity and related diseases : official journal of the American Society for Bariatric Surgery
BACKGROUND: The formulation of clinical recommendations pertaining to bariatric surgery is essential in guiding healthcare professionals. However, the extensive and continuously evolving body of literature in bariatric surgery presents considerable c...

Convolutional neural network for identifying common bile duct stones based on magnetic resonance cholangiopancreatography.

Clinical radiology
AIMS: To develop an auto-categorization system based on machine learning for three-dimensional magnetic resonance cholangiopancreatography (3D MRCP) to detect choledocholithiasis from healthy and symptomatic individuals.

Applying Common Spatial Pattern and Convolutional Neural Network to Classify Movements via EEG Signals.

Clinical EEG and neuroscience
Developing an electroencephalography (EEG)-based brain-computer interface (BCI) system is crucial to enhancing the control of external prostheses by accurately distinguishing various movements through brain signals. This innovation can provide comfor...

Frontal facial analysis of female celebrity attractiveness standards through artificial intelligence.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
The contemporary significance of celebrities' facial aesthetics underscores their heightened importance in shaping attractiveness standards. This retrospective study aimed to investigate the impact of patterns on aesthetic canons in the profile views...

Prediction of cardiovascular and renal risk among patients with apparent treatment-resistant hypertension in the United States using machine learning methods.

Journal of clinical hypertension (Greenwich, Conn.)
Apparent treatment-resistant hypertension (aTRH), defined as blood pressure (BP) that remains uncontrolled despite unconfirmed concurrent treatment with three antihypertensives, is associated with an increased risk of developing cardiovascular and re...

Artificial intelligence performance in clinical neurology queries: the ChatGPT model.

Neurological research
INTRODUCTION: The use of artificial intelligence technology is progressively expanding and advancing in the health and biomedical literature. Since its launch, ChatGPT has rapidly gained popularity and become one of the fastest-growing artificial int...

Empowering Graph Neural Networks with Block-Based Dual Adaptive Deep Adjustment for Drug Resistance-Related NcRNA Discovery.

Journal of chemical information and modeling
Drug resistance to chemotherapeutic agents remains a formidable challenge in cancer treatment, significantly impacting treatment efficacy. Extensive research has exposed the intimate involvement of noncoding RNAs (ncRNAs) in conferring resistance to ...