AIMC Topic: Humans

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Deep learning to assist composition classification and thyroid solid nodule diagnosis: a multicenter diagnostic study.

European radiology
OBJECTIVES: This study aimed to propose a deep learning (DL)-based framework for identifying the composition of thyroid nodules and assessing their malignancy risk.

Detection and severity quantification of pulmonary embolism with 3D CT data using an automated deep learning-based artificial solution.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to propose a deep learning-based approach to detect pulmonary embolism and quantify its severity using the Qanadli score and the right-to-left ventricle diameter (RV/LV) ratio on three-dimensional (3D) computed ...

Convolutional neural network misclassification analysis in oral lesions: an error evaluation criterion by image characteristics.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: This retrospective study analyzed the errors generated by a convolutional neural network (CNN) when performing automated classification of oral lesions according to their clinical characteristics, seeking to identify patterns in systemic e...

Deep Learning-Based Automated Labeling of Coronary Segments for Structured Reporting of Coronary Computed Tomography Angiography in Accordance With Society of Cardiovascular Computed Tomography Guidelines.

Journal of thoracic imaging
PURPOSE: To evaluate a novel deep learning (DL)-based automated coronary labeling approach for structured reporting of coronary artery disease according to the guidelines of the Society of Cardiovascular Computed Tomography (CT) on coronary CT angiog...

Natural Language Processing Applied to Clinical Documentation in Post-acute Care Settings: A Scoping Review.

Journal of the American Medical Directors Association
OBJECTIVES: To determine the scope of the application of natural language processing to free-text clinical notes in post-acute care and provide a foundation for future natural language processing-based research in these settings.

Identifying primary tumor site of origin for liver metastases via a combination of handcrafted and deep learning features.

The journal of pathology. Clinical research
Liver is one of the most common sites for metastases, which can occur on account of primary tumors from multiple sites of origin. Identifying the primary site of origin (PSO) of a metastasis can help in guiding therapeutic options for liver metastase...

Integrating street view images and deep learning to explore the association between human perceptions of the built environment and cardiovascular disease in older adults.

Social science & medicine (1982)
Understanding how built environment attributes affect health remains important. While many studies have explored the objective characteristics of built environments that affect health outcomes, few have examined the role of human perceptions of built...

One label is all you need: Interpretable AI-enhanced histopathology for oncology.

Seminars in cancer biology
Artificial Intelligence (AI)-enhanced histopathology presents unprecedented opportunities to benefit oncology through interpretable methods that require only one overall label per hematoxylin and eosin (H&E) slide with no tissue-level annotations. We...