AIMC Topic: Retrospective Studies

Clear Filters Showing 4661 to 4670 of 9989 articles

A comparison between robot-guided and stereotactic frame-based stereoelectroencephalography (SEEG) electrode implantation for drug-resistant epilepsy.

Journal of robotic surgery
The original stereoelectroencephalography frame-based implantation technique has been proven to be safe and effective. But this procedure is complicated and time-consuming. With the development of modern robotic technology, robot-guided intracerebral...

Evaluation of an Artificial Intelligence Model for Detection of Pneumothorax and Tension Pneumothorax in Chest Radiographs.

JAMA network open
IMPORTANCE: Early detection of pneumothorax, most often via chest radiography, can help determine need for emergent clinical intervention. The ability to accurately detect and rapidly triage pneumothorax with an artificial intelligence (AI) model cou...

A CT-Based Deep Learning Radiomics Nomogram to Predict Histological Grades of Head and Neck Squamous Cell Carcinoma.

Academic radiology
RATIONALE AND OBJECTIVES: Accurate pretreatment assessment of histological differentiation grade of head and neck squamous cell carcinoma (HNSCC) is crucial for prognosis evaluation. This study aimed to construct and validate a contrast-enhanced comp...

Robotic-assisted spine surgery allows for increased pedicle screw sizes while still improving safety as indicated by elevated triggered electromyographic thresholds.

Journal of robotic surgery
The present study used triggered electromyographic (EMG) testing as a tool to determine the safety of pedicle screw placement. In this Institutional Review Board exempt review, data from 151 consecutive patients (100 robotic; 51 non-robotic) who had ...

Primary bone tumor detection and classification in full-field bone radiographs via YOLO deep learning model.

European radiology
OBJECTIVES: Automatic bone lesions detection and classifications present a critical challenge and are essential to support radiologists in making an accurate diagnosis of bone lesions. In this paper, we aimed to develop a novel deep learning model ca...

3D CT-Inclusive Deep-Learning Model to Predict Mortality, ICU Admittance, and Intubation in COVID-19 Patients.

Journal of digital imaging
Chest CT is a useful initial exam in patients with coronavirus disease 2019 (COVID-19) for assessing lung damage. AI-powered predictive models could be useful to better allocate resources in the midst of the pandemic. Our aim was to build a deep-lear...

Comparison of robot-assisted partial nephrectomy with soft coagulation and double-layer technique for complex and non-complex tumors.

International journal of urology : official journal of the Japanese Urological Association
OBJECTIVES: To compare the postoperative outcomes of robot-assisted partial nephrectomy when only the inner layer is sutured (single-layer technique with soft coagulation) with those when sutures are placed in the inner and outer layers (double-layer...

[Robot-assisted rectal resections-Scoping review for levelĀ 1a evidence and retrospective analysis of in-clinic data].

Chirurgie (Heidelberg, Germany)
BACKGROUND: Robot-assisted rectal resections are said to overcome the known difficulties of laparoscopic rectal surgery through technical advantages, leading to better treatment results; however, published studies reported very heterogeneous results....

Robot-assisted versus thoracolaparoscopic oesophagectomy for locally advanced oesophageal squamous cell carcinoma after neoadjuvant chemoradiotherapy.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
INTRODUCTION: Robot-assisted oesophagectomy (RAE) and thoracolaparoscopic oesophagectomy (TLE) are surgical techniques for the treatment of oesophageal cancer. This study aimed to compare the perioperative and mid-term outcomes of RAE versus TLE for ...