AIMC Topic: Video Recording

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TUNeS: A Temporal U-Net With Self-Attention for Video-Based Surgical Phase Recognition.

IEEE transactions on bio-medical engineering
OBJECTIVE: To enable context-aware computer assistance in the operating room of the future, cognitive systems need to understand automatically which surgical phase is being performed by the medical team. The primary source of information for surgical...

[Application of multi-scale spatiotemporal networks in physiological signal and facial action unit measurement].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Multi-task learning (MTL) has demonstrated significant advantages in the field of physiological signal measurement. This approach enhances the model's generalization ability by sharing parameters and features between similar tasks, even in data-scarc...

Artificial Intelligence and Hand Hygiene Accuracy: A New Era in Infection Control for Dental Practices.

Clinical and experimental dental research
OBJECTIVE: The study aimed to assess the efficacy of an artificial intelligence (AI) model in evaluating hand hygiene (HH) performance compared to infection control auditors in dental clinics.

Automatic gesture recognition and evaluation in peg transfer tasks of laparoscopic surgery training.

Surgical endoscopy
BACKGROUND: Laparoscopic surgery training is gaining increasing importance. To release doctors from the burden of manually annotating videos, we proposed an automatic surgical gesture recognition model based on the Fundamentals of Laparoscopic Surger...

Deep learning-based intraoperative visual guidance model for ureter identification in laparoscopic sigmoidectomy.

Surgical endoscopy
BACKGROUND: Identifying the left ureter is a key step while performing laparoscopic sigmoid resection to prevent intraoperative injury and postoperative complications.

Attention in surgical phase recognition for endoscopic pituitary surgery: Insights from real-world data.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: Surgical Phase Recognition systems are used to support the automated documentation of a procedure and to provide the surgical team with real-time feedback, potentially improving surgical outcome and reducing adverse events. ...

Non-invasive diagnosis of lung diseases via multimodal feature extraction from breathing audio and chest dynamics.

Computers in biology and medicine
Early and accurate diagnosis of lung diseases is crucial for effective treatment. While traditional methods have limitations, audio analysis offers a promising non-invasive approach. However, existing studies often rely solely on acoustic features, n...

Learning Sequential Variation Information for Dynamic Facial Expression Recognition.

IEEE transactions on neural networks and learning systems
A multiscale sequence information fusion (MSSIF) method is presented for dynamic facial expression recognition (DFER) in video sequences. It exploits multiscale information by integrating features from individual frames, subsequences, and entire sequ...

FedBCD: Federated Ultrasound Video and Image Joint Learning for Breast Cancer Diagnosis.

IEEE transactions on medical imaging
Ultrasonography plays an essential role in breast cancer diagnosis. Current deep learning based studies train the models on either images or videos in a centralized learning manner, lacking consideration of joint benefits between two different modali...

Facial emotion based smartphone addiction detection and prevention using deep learning and video based learning.

Scientific reports
Smartphone addiction among students has emerged as a critical issue, negatively impacting their academic performance, emotional well-being, and social behavior. This paper introduces the Theory of Mind integrated with Video Modelling (TMVM) framework...