AIMC Topic: Humans

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Multicentric exploration of tool annotation in robotic surgery: lessons learned when starting a surgical artificial intelligence project.

Surgical endoscopy
BACKGROUND: Artificial intelligence (AI) holds tremendous potential to reduce surgical risks and improve surgical assessment. Machine learning, a subfield of AI, can be used to analyze surgical video and imaging data. Manual annotations provide verac...

Robot-assisted laparoscopic versus open partial nephrectomy for renal cell carcinoma in patients with severe chronic kidney disease.

International journal of urology : official journal of the Japanese Urological Association
OBJECTIVES: To compare surgical and functional outcomes between robot-assisted laparoscopic partial nephrectomy and open partial nephrectomy in patients with renal cell carcinoma with stage 4 chronic kidney disease.

Image Segmentation of Operative Neuroanatomy Into Tissue Categories Using a Machine Learning Construct and Its Role in Neurosurgical Training.

Operative neurosurgery (Hagerstown, Md.)
BACKGROUND: The complexity of the relationships among the structures within the brain makes efficient mastery of neuroanatomy difficult for medical students and neurosurgical residents. Therefore, there is a need to provide real-time segmentation of ...

Safety and risk factors of TINAVI robot-assisted percutaneous pedicle screw placement in spinal surgery.

Journal of orthopaedic surgery and research
OBJECTIVE: To determine the rates and risk factors of pedicle screw placement accuracy and the proximal facet joint violation (FJV) using TINAVI robot-assisted technique.

Early prediction of noninvasive ventilation failure after extubation: development and validation of a machine-learning model.

BMC pulmonary medicine
BACKGROUND: Noninvasive ventilation (NIV) has been widely used in critically ill patients after extubation. However, NIV failure is associated with poor outcomes. This study aimed to determine early predictors of NIV failure and to construct an accur...

Deep learning for predicting refractive error from multiple photorefraction images.

Biomedical engineering online
BACKGROUND: Refractive error detection is a significant factor in preventing the development of myopia. To improve the efficiency and accuracy of refractive error detection, a refractive error detection network (REDNet) is proposed that combines the ...

A comprehensive review of methods based on deep learning for diabetes-related foot ulcers.

Frontiers in endocrinology
BACKGROUND: Diabetes mellitus (DM) is a chronic disease with hyperglycemia. If not treated in time, it may lead to lower limb amputation. At the initial stage, the detection of diabetes-related foot ulcer (DFU) is very difficult. Deep learning has de...

A Case Study of Multiple Maintenance Efficacy in Gynaecological Surgery Assessed by Deep Learning.

Computational and mathematical methods in medicine
Deep learning is a new learning concept and a highly effective way of learning, which is still being explored in the field of nursing education. This paper analyses the effectiveness of interventions in perioperative gynaecological care using humanis...

Double-Balanced Loss for Imbalanced Colorectal Lesion Classification.

Computational and mathematical methods in medicine
Colorectal cancer has a high incidence rate in all countries around the world, and the survival rate of patients is improved by early detection. With the development of object detection technology based on deep learning, computer-aided diagnosis of c...