AIMC Topic: Retrospective Studies

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How to do robotic Ivor Lewis esophagectomy for lower third oesophageal cancer.

ANZ journal of surgery
Transthoracic subtotal esophagectomy with two-field lymph node (mediastinal and abdominal) and monobloc posterior mediastinectomy is called Ivor Lewis esophagectomy. This intervention requires an abdominal and thoracic time that is carried out here e...

A simple scoring model based on machine learning predicts intravenous immunoglobulin resistance in Kawasaki disease.

Clinical rheumatology
INTRODUCTION: In Kawasaki disease (KD), accurate prediction of intravenous immunoglobulin (IVIG) resistance is crucial to reduce a risk for developing coronary artery lesions.

Assessing the learning curve of robot-assisted total mesorectal excision: a multicenter study considering procedural safety, pathological safety, and efficiency.

International journal of colorectal disease
PURPOSE: Evidence regarding the learning curve of robot-assisted total mesorectal excision is scarce and of low quality. Case-mix is mostly not taken into account, and learning curves are based on operative time, while preferably clinical outcomes an...

An AI-Aided Diagnostic Framework for Hematologic Neoplasms Based on Morphologic Features and Medical Expertise.

Laboratory investigation; a journal of technical methods and pathology
A morphologic examination is essential for the diagnosis of hematological diseases. However, its conventional manual operation is time-consuming and laborious. Herein, we attempt to establish an artificial intelligence (AI)-aided diagnostic framework...

Abdominal and robotic sacrocolpopexy costs following implementation of enhanced recovery after surgery.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: To compare perioperative costs and morbidity between open and robotic sacrocolpopexy after implementation of enhanced recovery after surgery (ERAS) pathway.

Application of deep learning-based super-resolution to T1-weighted postcontrast gradient echo imaging of the chest.

La Radiologia medica
OBJECTIVES: A deep learning-based super-resolution for postcontrast volume-interpolated breath-hold examination (VIBE) of the chest was investigated in this study. Aim was to improve image quality, noise, artifacts and diagnostic confidence without c...

Deep learning of renal scans in children with antenatal hydronephrosis.

Journal of pediatric urology
INTRODUCTION: Antenatal hydronephrosis (ANH) is one of the most common anomalies identified on prenatal ultrasound, found in up to 4.5% of all pregnancies. Children with ANH are surveilled with repeated renal ultrasound and when there is high suspici...

Robot-assisted complex urinary tract reconstruction using intestinal segments: redefining the paradigm.

Journal of robotic surgery
Complex urinary tract reconstruction has significantly advanced with the increasing use of robot-assisted procedures. Robotic surgery aims to achieve the same outcomes as open surgery while minimizing morbidity by causing less blood loss, faster post...

Predicting N2 lymph node metastasis in presurgical stage I-II non-small cell lung cancer using multiview radiomics and deep learning method.

Medical physics
BACKGROUND: Accurate diagnosis of N2 lymph node status of the resectable stage I-II non-small cell lung cancer (NSCLC) before surgery is crucial, while there is lack of corresponding method clinically.

Predicting decompression surgery by applying multimodal deep learning to patients' structured and unstructured health data.

BMC medical informatics and decision making
BACKGROUND: Low back pain (LBP) is a common condition made up of a variety of anatomic and clinical subtypes. Lumbar disc herniation (LDH) and lumbar spinal stenosis (LSS) are two subtypes highly associated with LBP. Patients with LDH/LSS are often s...