AIMC Topic: Retrospective Studies

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Deep-Learning Reconstruction of High-Resolution CT Improves Interobserver Agreement for the Evaluation of Pulmonary Fibrosis.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
This study aimed to investigate whether deep-learning reconstruction (DLR) improves interobserver agreement in the evaluation of honeycombing for patients with interstitial lung disease (ILD) who underwent high-resolution computed tomography (CT) co...

Detection of periodontal bone loss patterns and furcation defects from panoramic radiographs using deep learning algorithm: a retrospective study.

BMC oral health
BACKGROUND: This retrospective study aimed to develop a deep learning algorithm for the interpretation of panoramic radiographs and to examine the performance of this algorithm in the detection of periodontal bone losses and bone loss patterns.

Radiological age assessment based on clavicle ossification in CT: enhanced accuracy through deep learning.

International journal of legal medicine
BACKGROUND: Radiological age assessment using reference studies is inherently limited in accuracy due to a finite number of assignable skeletal maturation stages. To overcome this limitation, we present a deep learning approach for continuous age ass...

Deep-learning model to improve histological grading and predict upstaging of atypical ductal hyperplasia / ductal carcinoma in situ on breast biopsy.

Histopathology
AIMS: Risk stratification of atypical ductal hyperplasia (ADH) and ductal carcinoma in situ (DCIS), diagnosed using breast biopsy, has great clinical significance. Clinical trials are currently exploring the possibility of active surveillance for low...

Impact of visceral fat area on short-term outcomes in robotic surgery for mid and low rectal cancer.

Journal of robotic surgery
Rectal cancer is one of the most prevalent cancers that arise in the digestive tract. The purpose of this retrospective study was to investigate the impact of visceral fat area (VFA) on postoperative outcomes in mid and low rectal cancer patients und...

Optimizing robotic thyroid surgery: lessons learned from an retrospective analysis of 104 cases.

Frontiers in endocrinology
BACKGROUND: Robotic assistance in thyroidectomy is a developing field that promises enhanced surgical precision and improved patient outcomes. This study investigates the impact of the da Vinci Surgical System on operative efficiency, learning curve,...

Validation of a deep learning system for the detection of diabetic retinopathy in Indigenous Australians.

The British journal of ophthalmology
BACKGROUND/AIMS: Deep learning systems (DLSs) for diabetic retinopathy (DR) detection show promising results but can underperform in racial and ethnic minority groups, therefore external validation within these populations is critical for health equi...