AIMC Topic: Prospective Studies

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Real-Time Identification of Pancreatic Cancer Cases Using Artificial Intelligence Developed on Danish Nationwide Registry Data.

JCO clinical cancer informatics
PURPOSE: Pancreatic cancer is expected to be the second leading cause of cancer-related deaths worldwide within few years. Most patients are not diagnosed in time for curative-intent treatment. Accelerating the time of diagnosis is a key component of...

Deep Learning Super-Resolution Reconstruction for Fast and Motion-Robust T2-weighted Prostate MRI.

Radiology
Background Deep learning (DL) reconstructions can enhance image quality while decreasing MRI acquisition time. However, DL reconstruction methods combined with compressed sensing for prostate MRI have not been well studied. Purpose To use an industry...

Long-term SARS-CoV-2 neutralizing antibody level prediction using multimodal deep learning: A prospective cohort study on longitudinal data in Wuhan, China.

Journal of medical virology
The ongoing epidemic of SARS-CoV-2 is taking a substantial financial and health toll on people worldwide. Assessing the level and duration of SARS-CoV-2 neutralizing antibody (Nab) would provide key information for government to make sound healthcare...

Representative Data Selection for Efficient Medical Incremental Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
To train a deep neural network relies on a large amount of annotated data. In special scenarios like industry defect detection and medical imaging, it is hard to collect sufficient labeled data all at once. Newly annotated data may arrive incremental...

Predicting pathological complete response to neoadjuvant systemic therapy for triple-negative breast cancers using deep learning on multiparametric MRIs.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
We trained and validated a deep learning model that can predict the treatment response to neoadjuvant systemic therapy (NAST) for patients with triple negative breast cancer (TNBC). Dynamic contrast enhanced (DCE) MRI and diffusion-weighted imaging (...

Using Real-Time Interaction Analysis to Explore Human-Robot Interaction.

Studies in health technology and informatics
Despite the increasing presence of social robots (SRs) in Human-Robot Interaction, there are few studies that quantify these interactions and explore children's attitudes by analyzing real-time data as they communicate with SRs. Therefore, we attempt...

Enabling Clinical Trials of Artificial Intelligence: Infrastructure for Heart Failure Predictions.

Studies in health technology and informatics
The last decade has seen a large increase in artificial intelligence research within healthcare. However, relatively few attempts of clinical trials have been made for such configurations. One of the main challenges arise in the extensive infrastruct...

Artificial Intelligence Solution for Chest Radiographs in Respiratory Outpatient Clinics: Multicenter Prospective Randomized Clinical Trial.

Annals of the American Thoracic Society
Artificial intelligence (AI)-assisted diagnosis imparts high accuracy to chest radiography (CXR) interpretation; however, its benefit for nonradiologist physicians in detecting lung lesions on CXR remains unclear. To investigate whether AI assistan...

Application of Deep Learning Models to Improve Ulcerative Colitis Endoscopic Disease Activity Scoring Under Multiple Scoring Systems.

Journal of Crohn's & colitis
BACKGROUND AND AIMS: Lack of clinical validation and inter-observer variability are two limitations of endoscopic assessment and scoring of disease severity in patients with ulcerative colitis [UC]. We developed a deep learning [DL] model to improve,...