Telemedicine has emerged as a transformative force in African surgical care, particularly in areas with scarce access to quality treatment. Despite challenges such as infrastructure deficits and personnel training, the implementation of telemedicine has demonstrated favorable outcomes. Increased adoption is evident in postsurgical care and doctor-patient consultations since the pandemic. While the potential for telesurgery […]
Category: Digital Surgery and Telemedicine
Machine learning models effectively predict appendicitis in emergencies
This proof-of-concept study reveals that machine learning models can predict appendicitis in patients with acute abdominal pain more accurately than traditional methods. With AUROCs of 0.919 and 0.923 when including laboratory test results, the models outperformed the Alvarado scoring system (AUROC of 0.824) and matched or exceeded the performance of emergency department physicians. These findings […]
Deep learning model predicts early recurrence in gastric cancer
A deep learning model (DLRMLP) integrating clinical factors outperformed traditional methods in predicting early recurrence of locally advanced gastric cancer (LAGC) post-gastrectomy. In a study involving 620 patients, DLRMLP achieved an AUC of 0.891 compared to 0.797 with conventional models. This model effectively stratified early recurrence-free survival, disease-free survival, and overall survival (all p < […]
Deep-learning model surpasses traditional methods in predicting HCC recurrence
A novel deep-learning model, Recurr-Net, showed superior accuracy in predicting hepatocellular carcinoma (HCC) recurrence post-surgery compared to histological microvascular invasion (MVI) and conventional clinical prediction scores. In a study of 1,231 patients, Recurr-Net achieved AUROC scores between 0.770 and 0.857 for internal validation, significantly better than MVI and various clinical risk scores. The model effectively […]
Digital reservation path enables efficient specialist appointments
A newly implemented structured reservation pathway (PRP) at Renji Hospital in Shanghai has improved access to specialist appointments for patients. Analysis of 58,271 applicants over two years revealed an overall pass rate of 34.8%, with significant demographic influences on outcomes. Age emerged as the primary predictor for approval through a random forest model with 92.31% […]
Fusion model predicts KRAS mutations in rectal cancer effectively
A study evaluated deep learning, radiomics, and fusion models to predict KRAS mutations in rectal cancer using endorectal ultrasound images from 304 patients. Among the models, the feature-based fusion model (dlrexpand10_fb) achieved the highest area under the receiver operating characteristic curve (AUC) of 0.896, indicating superior predictive performance. Additionally, incorporating peritumoral regions significantly improved the […]
AI Model Achieves High Accuracy in Panendoscopic Lesion Detection
An AI model was developed for the automatic detection of pleomorphic lesions during capsule endoscopy, achieving notable results across various gastrointestinal sites. The binary esophagus CNN attained 83.6% accuracy, while the gastric CNN reached 96.6%. The small bowel CNN excelled with 97.6% accuracy in identifying lesions with different hemorrhagic potentials. Additionally, the colonic CNN demonstrated […]
Telementoring enhances surgical skills in rural hospitals
A surgical telementoring system significantly improved surgical skills and job interest among medical students in rural Japan. Surgeons reported enhanced mental performance and reduced frustration when using the telementoring system. Furthermore, a substantial increase in interest for rural hospital work was noted among medical students after the experience, with more expressing a desire to pursue […]
XR technologies enhance surgical training effectiveness and acceptance
An umbrella review of 44 studies highlights the significant potential of extended reality (XR) technologies in surgical training, particularly for orthopedics, neurology, and laparoscopy. Findings revealed that XR improves surgical skills and procedural accuracy while reducing risks and operating room time. User-friendly systems increased accessibility for trainees across skill levels, and positive reinforcement from experienced […]
Deep-learning model predicts hepatocellular carcinoma recurrence effectively
A novel deep-learning model, Recurr-Net, significantly outperformed traditional methods in predicting hepatocellular carcinoma (HCC) recurrence post-curative surgery. Analyzed across 1,231 patients, Recurr-Net demonstrated an area under the receiver operating characteristic curve (AUROC) of 0.770 to 0.857 internally and 0.758 to 0.798 externally, while the historical microvascular invasion (MVI) showed much lower performance. This indicates Recurr-Net’s […]