AIMC Topic: Humans

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Applying artificial intelligence on EDA sensor data to predict stress on minimally invasive robotic-assisted surgery.

International journal of computer assisted radiology and surgery
PURPOSE: This study aims predicting the stress level based on the ergonomic (kinematic) and physiological (electrodermal activity-EDA, blood pressure and body temperature) parameters of the surgeon from their records collected in the previously immed...

Artificial Intelligence-based Segmentation of Residual Pancreatic Cancer in Resection Specimens Following Neoadjuvant Treatment (ISGPP-2): International Improvement and Validation Study.

The American journal of surgical pathology
Neoadjuvant therapy (NAT) has become routine in patients with borderline resectable pancreatic cancer. Pathologists examine pancreatic cancer resection specimens to evaluate the effect of NAT. However, an automated scoring system to objectively quant...

Machine-learning-based structural analysis of interactions between antibodies and antigens.

Bio Systems
Computational analysis of paratope-epitope interactions between antibodies and their corresponding antigens can facilitate our understanding of the molecular mechanism underlying humoral immunity and boost the design of new therapeutics for many dise...

Machine learning-based Cerebral Venous Thrombosis diagnosis with clinical data.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: Cerebral Venous Thrombosis (CVT) poses diagnostic challenges due to the variability in disease course and symptoms. The prognosis of CVT relies on early diagnosis. Our study focuses on developing a machine learning-based screening algorit...

Predicting long-term sleep deprivation using wearable sensors and health surveys.

Computers in biology and medicine
Sufficient sleep is essential for individual well-being. Inadequate sleep has been shown to have significant negative impacts on our attention, cognition, and mood. The measurement of sleep from in-bed physiological signals has progressed to where co...

Does clinical practice supported by artificial intelligence improve hypertension care management? A pilot systematic review.

Hypertension research : official journal of the Japanese Society of Hypertension
Although artificial intelligence (AI) is considered to be a promising tool, evidence for the effectiveness of AI-supported clinical practice for lowering blood pressure (BP) in the real world is scarce. We conducted a systematic review to elucidate w...

ESCCPred: a machine learning model for diagnostic prediction of early esophageal squamous cell carcinoma using autoantibody profiles.

British journal of cancer
BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a deadly cancer with no clinically ideal biomarkers for early diagnosis. The objective of this study was to develop and validate a user-friendly diagnostic tool for early ESCC detection.

Deep learning classification of ex vivo human colon tissues using spectroscopic optical coherence tomography.

Journal of biophotonics
Screening for colorectal cancer (CRC) with colonoscopy has improved patient outcomes; however, it remains the third leading cause of cancer-related mortality, novel strategies to improve screening are needed. Here, we propose an optical biopsy techni...

Ovarian cancer identification technology based on deep learning and second harmonic generation imaging.

Journal of biophotonics
Ovarian cancer is among the most common gynecological cancers and the eighth leading cause of cancer-related deaths among women worldwide. Surgery is among the most important options for cancer treatment. During surgery, a biopsy is generally require...