AIMC Topic: Retrospective Studies

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Keyhole Fenestration for Cerebrospinal Fluid Leaks in the Thoracic Spine: Quantification of Bone Removal and Microsurgical Anatomy.

Operative neurosurgery (Hagerstown, Md.)
BACKGROUND AND OBJECTIVE: A safe working trajectory is mandatory for spinal pathologies, especially in the midline, anterior to the spinal cord. For thoracic cerebrospinal fluid (CSF) leaks, we developed a minimally invasive keyhole fenestration. Thi...

Automated bone age assessment from knee joint by integrating deep learning and MRI-based radiomics.

International journal of legal medicine
Bone age assessment (BAA) is a crucial task in clinical, forensic, and athletic fields. Since traditional age estimation methods are suffered from potential radiation damage, this study aimed to develop and evaluate a deep learning radiomics method b...

APOLLO 11 Project, Consortium in Advanced Lung Cancer Patients Treated With Innovative Therapies: Integration of Real-World Data and Translational Research.

Clinical lung cancer
INTRODUCTION: Despite several therapeutic efforts, lung cancer remains a highly lethal disease. Novel therapeutic approaches encompass immune-checkpoint inhibitors, targeted therapeutics and antibody-drug conjugates, with different results. Several s...

A Short-Duration Gonadotropin-Releasing Hormone Stimulation Test for the Diagnosis of Central Precocious Puberty.

Medicina (Kaunas, Lithuania)
: The gonadotropin-releasing hormone (GnRH) stimulation test is the gold standard method for diagnosing central precocious puberty (CPP), although it requires multiple blood samplings over 120 min. This study aimed to evaluate if a shorter test may h...

CT-based deep learning model for predicting hospital discharge outcome in spontaneous intracerebral hemorrhage.

European radiology
OBJECTIVES: To predict the functional outcome of patients with intracerebral hemorrhage (ICH) using deep learning models based on computed tomography (CT) images.

Automatic detection, segmentation, and classification of primary bone tumors and bone infections using an ensemble multi-task deep learning framework on multi-parametric MRIs: a multi-center study.

European radiology
OBJECTIVES: To develop an ensemble multi-task deep learning (DL) framework for automatic and simultaneous detection, segmentation, and classification of primary bone tumors (PBTs) and bone infections based on multi-parametric MRI from multi-center.

Neurologic Statistical Prognostication and Risk Assessment for Kids on Extracorporeal Membrane Oxygenation-Neuro SPARK.

ASAIO journal (American Society for Artificial Internal Organs : 1992)
This study presents Neuro-SPARK, the first scoring system developed to assess the risk of neurologic injury in pediatric and neonatal patients on extracorporeal membrane oxygenation (ECMO). Using the extracorporeal life support organization (ELSO) re...

Deep learning for [F]fluorodeoxyglucose-PET-CT classification in patients with lymphoma: a dual-centre retrospective analysis.

The Lancet. Digital health
BACKGROUND: The rising global cancer burden has led to an increasing demand for imaging tests such as [F]fluorodeoxyglucose ([F]FDG)-PET-CT. To aid imaging specialists in dealing with high scan volumes, we aimed to train a deep learning artificial in...

Evaluating the Hounsfield unit assignment and dose differences between CT-based standard and deep learning-based synthetic CT images for MRI-only radiation therapy of the head and neck.

Journal of applied clinical medical physics
BACKGROUND: Magnetic resonance image only (MRI-only) simulation for head and neck (H&N) radiotherapy (RT) could allow for single-image modality planning with excellent soft tissue contrast. In the MRI-only simulation workflow, synthetic computed tomo...

Assessment of Quality Outcomes and the Learning Curve for Robot-Assisted Anatomical Lung Resections.

Journal of laparoendoscopic & advanced surgical techniques. Part A
To determine the perioperative quality assessment results and learning curves for robot-assisted anatomical lung resection. We analyzed the data of the initial 400 patients who underwent lobectomies or segmentectomies by 1 surgeon from January 2020...