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Recurrence

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Robotic transabdominal retromuscular rectus diastasis (r-TARRD) repair: a new approach.

Hernia : the journal of hernias and abdominal wall surgery
PURPOSE: The aim of this study is to present our innovative robotic approach for the treatment of rectus diastasis with concurrent primary or incisional ventral hernias.

Three-point mesh fixation in robot-assisted transabdominal preperitoneal (R-TAPP) repair of 208 inguinal hernias: preliminary results of a single-center consecutive series.

Langenbeck's archives of surgery
PURPOSE: The aim of this study was to assess the efficacy of our mesh fixation technique in robot-assisted transabdominal preperitoneal inguinal hernia repair (R-TAPP). The primary outcome was the recurrence rate. Secondary outcomes were postoperativ...

Robotic redo Heller myotomy: how I do it?

Langenbeck's archives of surgery
BACKGROUND: Despite the high success rate associated with Heller myotomy in the treatment of primary achalasia, symptom persistence or relapse occurs in approximately 10-20% of patients. Unfortunately, the ideal treatment after failed myotomy is not ...

Deep Learning Analysis of Histologic Images from Intestinal Specimen Reveals Adipocyte Shrinkage and Mast Cell Infiltration to Predict Postoperative Crohn Disease.

The American journal of pathology
Most patients with Crohn disease (CD), a chronic inflammatory gastrointestinal disease, experience recurrence despite treatment, including surgical resection. However, methods for predicting recurrence remain unclear. This study aimed to predict post...

The Prediction of Fall Circumstances Among Patients in Clinical Care - A Retrospective Observational Study.

Studies in health technology and informatics
Standardized fall risk scores have not proven to reliably predict falls in clinical settings. Machine Learning offers the potential to increase the accuracy of such predictions, possibly vastly improving care for patients at high fall risks. We devel...

Predicting Atrial Fibrillation Recurrence by Combining Population Data and Virtual Cohorts of Patient-Specific Left Atrial Models.

Circulation. Arrhythmia and electrophysiology
BACKGROUND: Current ablation therapy for atrial fibrillation is suboptimal, and long-term response is challenging to predict. Clinical trials identify bedside properties that provide only modest prediction of long-term response in populations, while ...

Personalized application of machine learning algorithms to identify pediatric patients at risk for recurrent ureteropelvic junction obstruction after dismembered pyeloplasty.

World journal of urology
PURPOSE: To develop a model that predicts whether a child will develop a recurrent obstruction after pyeloplasty, determine their survival risk score, and expected time to re-intervention using machine learning (ML).

Deep Learning-Based Recurrence Prediction of Atrial Fibrillation After Catheter Ablation.

Circulation journal : official journal of the Japanese Circulation Society
BACKGROUND: Radiofrequency catheter ablation (RFCA) is an effective therapy for atrial fibrillation (AF). However, it the problem of AF recurrence remains. This study investigates whether a deep convolutional neural network (CNN) can accurately predi...

Robot-assisted vs. laparoscopic repair of complete upside-down stomach hiatal hernia (the RATHER-study): a prospective comparative single center study.

Surgical endoscopy
BACKGROUND: Complete upside-down stomach (cUDS) hernias are a subgroup of large hiatal hernias characterized by high risk of life-threatening complications and technically challenging surgical repair including complex mediastinal dissection. In a pro...