AIMC Topic: Humans

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From Compressed-Sensing to Deep Learning MR: Comparative Biventricular Cardiac Function Analysis in a Patient Cohort.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Conventional segmented, retrospectively gated cine (Conv-cine) is challenged in patients with breath-hold difficulties. Compressed sensing (CS) has shown values in cine imaging but generally requires long reconstruction time. Recent artif...

Clinical Applications, Challenges, and Recommendations for Artificial Intelligence in Musculoskeletal and Soft-Tissue Ultrasound: Expert Panel Narrative Review.

AJR. American journal of roentgenology
Artificial intelligence (AI) is increasingly used in clinical practice for musculoskeletal imaging tasks, such as disease diagnosis and image reconstruction. AI applications in musculoskeletal imaging have focused primarily on radiography, CT, and MR...

A novel approach to quantify calcifications of thyroid nodules in US images based on deep learning: predicting the risk of cervical lymph node metastasis in papillary thyroid cancer patients.

European radiology
OBJECTIVE: Based on ultrasound (US) images, this study aimed to detect and quantify calcifications of thyroid nodules, which are regarded as one of the most important features in US diagnosis of thyroid cancer, and to further investigate the value of...

Prognostic impact of deep learning-based quantification in clinical stage 0-I lung adenocarcinoma.

European radiology
OBJECTIVES: To evaluate the performance of automatic deep learning (DL) algorithm for size, mass, and volume measurements in predicting prognosis of lung adenocarcinoma (LUAD) and compared with manual measurements.

Diagnostic radiology and its future: what do clinicians need and think?

European radiology
OBJECTIVE: To investigate the view of clinicians on diagnostic radiology and its future.

Multi-institutional PET/CT image segmentation using federated deep transformer learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Generalizable and trustworthy deep learning models for PET/CT image segmentation necessitates large diverse multi-institutional datasets. However, legal, ethical, and patient privacy issues challenge sharing of datasets betw...

A deep learning-based drug repurposing screening and validation for anti-SARS-CoV-2 compounds by targeting the cell entry mechanism.

Biochemical and biophysical research communications
The recent outbreak of Corona Virus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a severe threat to the global public health and economy, however, effective drugs to treat COVID-19 are still ...

Artificial intelligence in pharmaceutical regulatory affairs.

Drug discovery today
Artificial intelligence (AI) refers to the ability of a computer to carry out tasks associated with human intelligence, including thinking, discovering, and learning from prior experience. AI can be integrated to simplify the complexity of pharmaceut...

Pectoralis muscle predicts distant metastases in breast cancer by deep learning radiomics.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Sarcopenia is associated with a poor prognosis in patients with breast cancer (BC). Currently, there are few quantitative assessments carried out between muscle biomarkers and distant metastasis using existing methods.