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Recurrence

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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 ...

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...

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 ...

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...

Outcomes of open transverse abdominis release for ventral hernias: a systematic review, meta-analysis and meta-regression of factors affecting them.

Hernia : the journal of hernias and abdominal wall surgery
OBJECTIVES: The primary objectives were to evaluate Surgical Site Occurrences (SSO) and Surgical Site Occurrences requiring procedural Intervention (SSOPI) after open transversus abdominis release and to study various factors affecting it. Secondary ...

A Model of Normality Inspired Deep Learning Framework for Depression Relapse Prediction Using Audiovisual Data.

Computer methods and programs in biomedicine
BACKGROUND: Depression (Major Depressive Disorder) is one of the most common mental illnesses. According to the World Health Organization, more than 300 million people in the world are affected. A first depressive episode can be solved by a spontaneo...

Estimating individual treatment effect on disability progression in multiple sclerosis using deep learning.

Nature communications
Disability progression in multiple sclerosis remains resistant to treatment. The absence of a suitable biomarker to allow for phase 2 clinical trials presents a high barrier for drug development. We propose to enable short proof-of-concept trials by ...

Deep learning-based automated quantification of goblet cell mucus using histological images as a predictor of clinical relapse of ulcerative colitis with endoscopic remission.

Journal of gastroenterology
BACKGROUND: Mucin depletion is one of the histological indicators of clinical relapse among patients with ulcerative colitis (UC). Mucin depletion is evaluated semiquantitatively by pathologists using histological images. Therefore, the interobserver...