AIMC Topic: Humans

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Radiomics for prediction of perineural invasion in colorectal cancer: a systematic review and meta-analysis.

Abdominal radiology (New York)
BACKGROUND: Perineural invasion (PNI) in colorectal cancer (CRC) is a significant prognostic factor associated with poor outcomes. Radiomics, which involves extracting quantitative features from medical imaging, has emerged as a potential tool for pr...

Enhanced accuracy and stability in automated intra-pancreatic fat deposition monitoring of type 2 diabetes mellitus using Dixon MRI and deep learning.

Abdominal radiology (New York)
PURPOSE: Intra-pancreatic fat deposition (IPFD) is closely associated with the onset and progression of type 2 diabetes mellitus (T2DM). We aimed to develop an accurate and automated method for assessing IPFD on multi-echo Dixon MRI.

Automated vs manual cardiac MRI planning: a single-center prospective evaluation of reliability and scan times.

European radiology
OBJECTIVES: Evaluating the impact of an AI-based automated cardiac MRI (CMR) planning software on procedure errors and scan times compared to manual planning alone.

Stress radiography of medial knee instability provides a reliable correlation with the severity of injury and medial joint space opening-A robotic biomechanical cadaveric study.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: The medial collateral ligament (MCL), and posterior oblique ligament (POL) are the primary valgus stabilisers of the knee, and clinical examinations in grading valgus instability can be inherently subjective. Stress radiography of medial-sid...

Embracing the Future of Clinical Trials in Radiation Therapy: An NRG Oncology CIRO Technology Retreat Whitepaper on Pioneering Technologies and AI-Driven Solutions.

International journal of radiation oncology, biology, physics
This white paper examines the potential of pioneering technologies and artificial intelligence-driven solutions in advancing clinical trials involving radiation therapy. As the field of radiation therapy evolves, the integration of cutting-edge appro...

An overview of the use of cutting-edge artificial intelligence (AI) modeling to produce synthetic medical data (SMD) in decentralized clinical machine learning (ML) for ovarian cancer(OC) and ovarian lymphoma(OL).

Journal of ultrasound
AIM: o point out how novel analysis tools of AI can make sense of the data acquired during OL and OC diagnosis and treatment in an effort to help improve and standardize the patient pathway for these disease.

CTCNet: a fine-grained classification network for fluorescence images of circulating tumor cells.

Medical & biological engineering & computing
The identification and categorization of circulating tumor cells (CTCs) in peripheral blood are imperative for advancing cancer diagnostics and prognostics. The intricacy of various CTCs subtypes, coupled with the difficulty in developing exhaustive ...

Automatic skeletal maturity grading from pelvis radiographs by deep learning for adolescent idiopathic scoliosis.

Medical & biological engineering & computing
Adolescent idiopathic scoliosis (AIS) is a three-dimensional spine deformity governed of the spine. A child's Risser stage of skeletal maturity must be carefully considered for AIS evaluation and treatment. However, there are intra-observer and inter...

SAC-BL: A hypothesis testing framework for unsupervised visual anomaly detection and location.

Neural networks : the official journal of the International Neural Network Society
Reconstruction-based methods achieve promising performance for visual anomaly detection (AD), relying on the underlying assumption that the anomalies cannot be accurately reconstructed. However, this assumption does not always hold, especially when s...