AIMC Topic: Adult

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CT-based intratumoral and peritumoral deep transfer learning features prediction of lymph node metastasis in non-small cell lung cancer.

Journal of X-ray science and technology
BACKGROUND: The main metastatic route for lung cancer is lymph node metastasis, and studies have shown that non-small cell lung cancer (NSCLC) has a high risk of lymph node infiltration.

Automatic detection of thyroid nodules with a real-time artificial intelligence system in a real clinical scenario and the associated influencing factors.

Clinical hemorheology and microcirculation
BACKGROUND: At present, most articles mainly focused on the diagnosis of thyroid nodules by using artificial intelligence (AI), and there was little research on the detection performance of AI in thyroid nodules.

Implementation of a robot-mediated upper limb rehabilitation protocol for a customized treatment after stroke: A retrospective analysis.

NeuroRehabilitation
BACKGROUND: Many authors have emphasized the need for individualized treatments in rehabilitation, but no tailored robotic rehabilitation protocol for stroke patients has been established yet.

Detection of anemic condition in patients from clinical markers and explainable artificial intelligence.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Anaemia is a commonly known blood illness worldwide. Red blood cell (RBC) count or oxygen carrying capability being insufficient are two ways to describe anaemia. This disorder has an impact on the quality of life. If anaemia is detected ...

Peri-lesion regions in differentiating suspicious breast calcification-only lesions specifically on contrast enhanced mammography.

Journal of X-ray science and technology
PURPOSE: The explore the added value of peri-calcification regions on contrast-enhanced mammography (CEM) in the differential diagnosis of breast lesions presenting as only calcification on routine mammogram.

Development and validation of a clinical prediction model for glioma grade using machine learning.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Histopathological evaluation is currently the gold standard for grading gliomas; however, this technique is invasive.

Deep learning-based differentiation of peripheral high-flow and low-flow vascular malformations in T2-weighted short tau inversion recovery MRI.

Clinical hemorheology and microcirculation
BACKGROUND: Differentiation of high-flow from low-flow vascular malformations (VMs) is crucial for therapeutic management of this orphan disease.

A CT-based Deep Learning Model for Predicting Subsequent Fracture Risk in Patients with Hip Fracture.

Radiology
Background Patients have the highest risk of subsequent fractures in the first few years after an initial fracture, yet models to predict short-term subsequent risk have not been developed. Purpose To develop and validate a deep learning prediction m...

Erector Spinae Plane Block versus Transversus Abdominis Plane Block for Robotic Inguinal Hernia Repair: A Blinded, Active-Controlled, Randomized Trial.

Pain physician
BACKGROUND: Regional anesthetic nerve blocks are widely used in the treatment of pain after outpatient surgery to reduce opioid consumption. Erector spinae plane (ESP) block is a recently described technique with promising results in different scenar...

Application of Machine-learning based on Radiomics Features in Differential Diagnosis of Superficial Lymphadenopathy.

Current medical imaging
OBJECTIVE: The accurate diagnosis of superficial lymphadenopathy is challenging. We aim to explore a non-invasive and accurate machine-learning method for distinguishing benign lymph nodes, lymphoma, and metastatic lymph nodes.