AIMC Topic: Algorithms

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Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor Segmentation.

Radiology. Artificial intelligence
Purpose To present results from a literature survey on practices in deep learning segmentation algorithm evaluation and perform a study on expert quality perception of brain tumor segmentation. Materials and Methods A total of 180 articles reporting ...

Comparison of Commercial AI Software Performance for Radiograph Lung Nodule Detection and Bone Age Prediction.

Radiology
Background Multiple commercial artificial intelligence (AI) products exist for assessing radiographs; however, comparable performance data for these algorithms are limited. Purpose To perform an independent, stand-alone validation of commercially ava...

Research on breast cancer pathological image classification method based on wavelet transform and YOLOv8.

Journal of X-ray science and technology
 Breast cancer is one of the cancers with high morbidity and mortality in the world, which is a serious threat to the health of women. With the development of deep learning, the recognition about computer-aided diagnosis technology is getting higher ...

Diagnosis of Covid-19 from CT slices using Whale Optimization Algorithm, Support Vector Machine and Multi-Layer Perceptron.

Journal of X-ray science and technology
BACKGROUND: The coronavirus disease 2019 is a serious and highly contagious disease caused by infection with a newly discovered virus, named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

FDA Review of Radiologic AI Algorithms: Process and Challenges.

Radiology
A Food and Drug Administration (FDA)-cleared artificial intelligence (AI) algorithm misdiagnosed a finding as an intracranial hemorrhage in a patient, who was finally diagnosed with an ischemic stroke. This scenario highlights a notable failure mode ...

Breast cancer detection employing stacked ensemble model with convolutional features.

Cancer biomarkers : section A of Disease markers
Breast cancer is a major cause of female deaths, especially in underdeveloped countries. It can be treated if diagnosed early and chances of survival are high if treated appropriately and timely. For timely and accurate automated diagnosis, machine l...

Spatial Omics Driven Crossmodal Pretraining Applied to Graph-based Deep Learning for Cancer Pathology Analysis.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Graph-based deep learning has shown great promise in cancer histopathology image analysis by contextualizing complex morphology and structure across whole slide images to make high quality downstream outcome predictions (ex: prognostication). These m...

Leveraging 3D Echocardiograms to Evaluate AI Model Performance in Predicting Cardiac Function on Out-of-Distribution Data.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Advancements in medical imaging and artificial intelligence (AI) have revolutionized the field of cardiac diagnostics, providing accurate and efficient tools for assessing cardiac function. AI diagnostics claims to improve upon the human-to-human var...

Session Introduction: Artificial Intelligence in Clinical Medicine: Generative and Interactive Systems at the Human-Machine Interface.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Artificial Intelligence (AI) models are substantially enhancing the capability to analyze complex and multi-dimensional datasets. Generative AI and deep learning models have demonstrated significant advancements in extracting knowledge from unstructu...

The Future of MR-Guided Radiation Therapy.

Seminars in radiation oncology
Magnetic resonance image guided radiation therapy (MRIgRT) is a relatively new technology that has already shown outcomes benefits but that has not yet reached its clinical potential. The improved soft-tissue contrast provided with MR, coupled with t...