AIMC Topic: Retrospective Studies

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Video-Based Detection of Generalized Tonic-Clonic Seizures Using Deep Learning.

IEEE journal of biomedical and health informatics
Timely detection of seizures is crucial to implement optimal interventions, and may help reduce the risk of sudden unexpected death in epilepsy (SUDEP) in patients with generalized tonic-clonic seizures (GTCSs). While video-based automated seizure de...

Development and validation of a deep learning system to classify aetiology and predict anatomical outcomes of macular hole.

The British journal of ophthalmology
AIMS: To develop a deep learning (DL) model for automatic classification of macular hole (MH) aetiology (idiopathic or secondary), and a multimodal deep fusion network (MDFN) model for reliable prediction of MH status (closed or open) at 1 month afte...

Deep learning in knee imaging: a systematic review utilizing a Checklist for Artificial Intelligence in Medical Imaging (CLAIM).

European radiology
PURPOSE: Our purposes were (1) to explore the methodologic quality of the studies on the deep learning in knee imaging with CLAIM criterion and (2) to offer our vision for the development of CLAIM to assure high-quality reports about the application ...

Development of novel artificial intelligence systems to predict facial morphology after orthognathic surgery and orthodontic treatment in Japanese patients.

Scientific reports
From a socio-psychological standpoint, improving the morphology of the facial soft-tissues is regarded as an important therapeutic goal in modern orthodontic treatment. Currently, many of the algorithms used in commercially available software program...

Pure laparoscopic versus robotic liver resections: Multicentric propensity score-based analysis with stratification according to difficulty scores.

Journal of hepato-biliary-pancreatic sciences
BACKGROUND: The benefits of pure laparoscopic and robot-assisted liver resections (LLR and RALR) are known in comparison to open surgery. The aim of the present retrospective comparative study is to investigate the role of RALR and LLR according to d...

Surgical outcomes of robot-assisted laparoscopic partial nephrectomy for cystic renal cell carcinoma.

Journal of robotic surgery
To compare the surgical outcomes of robot-assisted partial nephrectomy (RAPN) between patients with cystic renal cell carcinoma (cRCC) and those with solid RCC (sRCC). We retrospectively analyzed 1065 patients who underwent RAPN between 2013 and 2020...

Deep Learning to Determine the Activity of Pulmonary Tuberculosis on Chest Radiographs.

Radiology
Background Determining the activity of pulmonary tuberculosis on chest radiographs is difficult. Purpose To develop a deep learning model to identify active pulmonary tuberculosis on chest radiographs. Materials and Methods Chest radiographs were ret...

Patterns of Metastatic Disease in Patients with Cancer Derived from Natural Language Processing of Structured CT Radiology Reports over a 10-year Period.

Radiology
Background Patterns of metastasis in cancer are increasingly relevant to prognostication and treatment planning but have historically been documented by means of autopsy series. Purpose To show the feasibility of using natural language processing (NL...

Artificial Intelligence-Based Prediction of Lung Cancer Risk Using Nonimaging Electronic Medical Records: Deep Learning Approach.

Journal of medical Internet research
BACKGROUND: Artificial intelligence approaches can integrate complex features and can be used to predict a patient's risk of developing lung cancer, thereby decreasing the need for unnecessary and expensive diagnostic interventions.

Robotic versus laparoscopic right hemicolectomy: a case-matched study.

Journal of robotic surgery
The current gold standard surgical treatment for right colonic malignancy is the laparoscopic right hemicolectomy (LRH). However, laparoscopic surgery has limitations which can be overcome by robotic surgery. The benefits of robotics for rectal cance...