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Sample Size Requirements to Test Subgroup-Specific Treatment Effects in Cluster-Randomized Trials
Cluster-randomized trials (CRTs) often allocate intact clusters of participants to treatment or control conditions and are increasingly used to...
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Application of Machine Learning to Ultrasonography in Identifying Anatomical Landmarks for Cricothyroidotomy Among Female Adults: A Multi-center Prospective Observational Study
We aimed to develop machine learning (ML)-based algorithms to assist physicians in ultrasound-guided localization of cricoid cartilage (CC) and...
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Precise highlighting of the pancreas by semantic segmentation during robot-assisted gastrectomy: visual assistance with artificial intelligence for surgeons
BackgroundA postoperative pancreatic fistula (POPF) is a critical complication of radical gastrectomy for gastric cancer, mainly because surgeons...
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Deep learning models for automatic tumor segmentation and total tumor volume assessment in patients with colorectal liver metastases
BackgroundWe developed models for tumor segmentation to automate the assessment of total tumor volume (TTV) in patients with colorectal liver...
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Deep learning on tertiary lymphoid structures in hematoxylin-eosin predicts cancer prognosis and immunotherapy response
Tertiary lymphoid structures (TLSs) have been associated with favorable immunotherapy responses and prognosis in various cancers. Despite their...
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SAA-SDM: Neural Networks Faster Learned to Segment Organ Images
In the field of medicine, rapidly and accurately segmenting organs in medical images is a crucial application of computer technology. This paper...
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Automatic segmentation of 15 critical anatomical labels and measurements of cardiac axis and cardiothoracic ratio in fetal four chambers using nnU-NetV2
BackgroundAccurate segmentation of critical anatomical structures in fetal four-chamber view images is essential for the early detection of...
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Improving the Quantitative Analysis of Breast Microcalcifications: A Multiscale Approach
Accurate characterization of microcalcifications (MCs) in 2D digital mammography is a necessary step toward reducing the diagnostic uncertainty...
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GLGFormer: Global Local Guidance Network for Mucosal Lesion Segmentation in Gastrointestinal Endoscopy Images
Automatic mucosal lesion segmentation is a critical component in computer-aided clinical support systems for endoscopic image analysis. Image...
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Gaze behavior is related to objective technical skills assessment during virtual reality simulator-based surgical training: a proof of concept
PurposeSimulation-based training allows surgical skills to be learned safely. Most virtual reality-based surgical simulators address technical skills...
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Artificial intelligence-aided lytic spinal bone metastasis classification on CT scans
PurposeSpinal bone metastases directly affect quality of life, and patients with lytic-dominant lesions are at high risk for neurological symptoms...
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DBH-YOLO: a surgical instrument detection method based on feature separation in laparoscopic surgery
PurposeAccurately locating and analysing surgical instruments in laparoscopic surgical videos can assist doctors in postoperative quality assessment....
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Automatic Spine Segmentation and Parameter Measurement for Radiological Analysis of Whole-Spine Lateral Radiographs Using Deep Learning and Computer Vision
Radiographic examination is essential for diagnosing spinal disorders, and the measurement of spino-pelvic parameters provides important information...
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Supraspinatus extraction from MRI based on attention-dense spatial pyramid UNet network
BackgroundWith potential of deep learning in musculoskeletal image interpretation being explored, this paper focuses on the common site of rotator...
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Patient-specific placental vessel segmentation with limited data
A major obstacle in applying machine learning for medical fields is the disparity between the data distribution of the training images and the data...
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Utility of Artificial Intelligence for Real-Time Anatomical Landmark Identification in Ultrasound-Guided Thoracic Paravertebral Block
Thoracic paravertebral block (TPVB) is a common method of inducing perioperative analgesia in thoracic and abdominal surgery. Identifying anatomical...
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Automated Quantification of Total Cerebral Blood Flow from Phase-Contrast MRI and Deep Learning
Knowledge of input blood to the brain, which is represented as total cerebral blood flow (tCBF), is important in evaluating brain health....
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A spatio-temporal network for video semantic segmentation in surgical videos
PurposeSemantic segmentation in surgical videos has applications in intra-operative guidance, post-operative analytics and surgical education. Models...
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Deep learning algorithm (YOLOv7) for automated renal mass detection on contrast-enhanced MRI: a 2D and 2.5D evaluation of results
IntroductionAccurate diagnosis and treatment of kidney tumors greatly benefit from automated solutions for detection and classification on MRI. In...
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Deep CTS: a Deep Neural Network for Identification MRI of Carpal Tunnel Syndrome
Carpal tunnel syndrome (CTS) is a common peripheral nerve disease in adults; it can cause pain, numbness, and even muscle atrophy and will adversely...
