AIMC Topic: Retrospective Studies

Clear Filters Showing 4141 to 4150 of 9989 articles

Differentiation between Phyllodes Tumors and Fibroadenomas through Breast Ultrasound: Deep-Learning Model Outperforms Ultrasound Physicians.

Sensors (Basel, Switzerland)
The preoperative differentiation of breast phyllodes tumors (PTs) from fibroadenomas (FAs) plays a critical role in identifying an appropriate surgical treatment. Although several imaging modalities are available, reliable differentiation between PT ...

A deep learning model enables accurate prediction and quantification of pulmonary edema from chest X-rays.

Critical care (London, England)
BACKGROUND: A quantitative assessment of pulmonary edema is important because the clinical severity can range from mild impairment to life threatening. A quantitative surrogate measure, although invasive, for pulmonary edema is the extravascular lung...

Artificial intelligence, big data and heart transplantation: Actualities.

International journal of medical informatics
BACKGROUND: As diagnostic and prognostic models developed by traditional statistics perform poorly in real-world, artificial intelligence (AI) and Big Data (BD) may improve the supply chain of heart transplantation (HTx), allocation opportunities, co...

Multiscale deep learning framework captures systemic immune features in lymph nodes predictive of triple negative breast cancer outcome in large-scale studies.

The Journal of pathology
The suggestion that the systemic immune response in lymph nodes (LNs) conveys prognostic value for triple-negative breast cancer (TNBC) patients has not previously been investigated in large cohorts. We used a deep learning (DL) framework to quantify...

Robot-assisted adrenalectomy using a hinotori surgical robot system: Report of first series of six cases.

Asian journal of endoscopic surgery
AIM: The hinotori surgical robot system, a newly launched platform, has already been utilized in several urological robotic surgeries; however, limited information is available in terms of its feasibility and safety in each type of surgery. The objec...

Effects of tracer position on screw placement technique in robot-assisted posterior spine surgery: a case-control study.

BMC musculoskeletal disorders
INTRODUCTION: Robot-assisted spine surgery is increasingly used in clinical work, and the installation of tracers as a key step in robotic surgery has rarely been studied.

Graphic Intelligent Diagnosis of Hypoxic-Ischemic Encephalopathy Using MRI-Based Deep Learning Model.

Neonatology
INTRODUCTION: Heterogeneous MRI manifestations restrict the efficiency and consistency of neuroradiologists in diagnosing hypoxic-ischemic encephalopathy (HIE) due to complex injury patterns. This study aimed to develop and validate an intelligent HI...

Deep learning-based screening tool for rotator cuff tears on shoulder radiography.

Journal of orthopaedic science : official journal of the Japanese Orthopaedic Association
BACKGROUND: Early diagnosis of rotator cuff tears is essential for appropriate and timely treatment. Although radiography is the most used technique in clinical practice, it is difficult to accurately rule out rotator cuff tears as an initial imaging...

Prenatal Diagnosis of Placenta Accreta Spectrum Disorders: Deep Learning Radiomics of Pelvic MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Diagnostic performance of placenta accreta spectrum (PAS) by prenatal MRI is unsatisfactory. Deep learning radiomics (DLR) has the potential to quantify the MRI features of PAS.

Development of a deep-learning model for classification of LI-RADS major features by using subtraction images of MRI: a preliminary study.

Abdominal radiology (New York)
PURPOSE: Liver Imaging Reporting and Data System (LI-RADS) is limited by interreader variability. Thus, our study aimed to develop a deep-learning model for classifying LI-RADS major features using subtraction images using magnetic resonance imaging ...