AIMC Topic: Retrospective Studies

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A novel deep learning-based quantification of serial chest computed tomography in Coronavirus Disease 2019 (COVID-19).

Scientific reports
This study aims to explore and compare a novel deep learning-based quantification with the conventional semi-quantitative computed tomography (CT) scoring for the serial chest CT scans of COVID-19. 95 patients with confirmed COVID-19 and a total of 4...

Behavioral and neurophysiological effects of an intensified robot-assisted therapy in subacute stroke: a case control study.

Journal of neuroengineering and rehabilitation
BACKGROUND: Physical training is able to induce changes at neurophysiological and behavioral level associated with performance changes for the trained movements. The current study explores the effects of an additional intense robot-assisted upper ext...

A deep learning model for diagnosing dystrophinopathies on thigh muscle MRI images.

BMC neurology
BACKGROUND: Dystrophinopathies are the most common type of inherited muscular diseases. Muscle biopsy and genetic tests are effective to diagnose the disease but cost much more than primary hospitals can reach. The more available muscle MRI is promis...

Analyzing Surgical Treatment of Intestinal Obstruction in Children with Artificial Intelligence.

Computational and mathematical methods in medicine
Intestinal obstruction is a common surgical emergency in children. However, it is challenging to seek appropriate treatment for childhood ileus since many diagnostic measures suitable for adults are not applicable to children. The rapid development o...

Additional value of deep learning computed tomographic angiography-based fractional flow reserve in detecting coronary stenosis and predicting outcomes.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Deep learning (DL) has achieved great success in medical imaging and could be utilized for the non-invasive calculation of fractional flow reserve (FFR) from coronary computed tomographic angiography (CCTA) (CT-FFR).

Quantitative evaluation of chronically obstructed kidneys from noncontrast computed tomography based on deep learning.

European journal of radiology
OBJECTIVE: To quantitatively report renal parenchymal volume (RPV), renal sinus volume (RSV), and renal parenchymal density (RPD) for chronically obstructed kidneys from noncontrast computed tomography (NCCT).

A deep learning framework for F-FDG PET imaging diagnosis in pediatric patients with temporal lobe epilepsy.

European journal of nuclear medicine and molecular imaging
PURPOSE: Epilepsy is one of the most disabling neurological disorders, which affects all age groups and often results in severe consequences. Since misdiagnoses are common, many pediatric patients fail to receive the correct treatment. Recently, F-fl...

Robotic transanal minimally invasive surgery: a case series.

Surgical endoscopy
INTRODUCTION: This study describes the experience with robot-assisted transanal minimally invasive surgery (rTAMIS) at a single institution. TAMIS has become a popular minimally invasive technique for local excision of well-selected rectal lesions. r...

Pancreatic fistulas following distal pancreatectomy are unrelated to the texture quality of the pancreas.

Langenbeck's archives of surgery
PURPOSE: The relevance of pancreatic texture for pancreatic fistula (POPF) formation after distal pancreatectomy (DP) remains ill defined. Recent POPF definition adjustments and common subjective pancreatic texture assessment are further drawbacks in...