AI Medical Compendium Topic

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Clinical risk prediction models and informative cluster size: Assessing the performance of a suicide risk prediction algorithm.

Biometrical journal. Biometrische Zeitschrift
Clinical visit data are clustered within people, which complicates prediction modeling. Cluster size is often informative because people receiving more care are less healthy and at higher risk of poor outcomes. We used data from seven health systems ...

COVID-19 diagnosis by routine blood tests using machine learning.

Scientific reports
Physicians taking care of patients with COVID-19 have described different changes in routine blood parameters. However, these changes hinder them from performing COVID-19 diagnoses. We constructed a machine learning model for COVID-19 diagnosis that ...

End-to-end deep learning for recognition of ploidy status using time-lapse videos.

Journal of assisted reproduction and genetics
PURPOSE: Our retrospective study is to investigate an end-to-end deep learning model in identifying ploidy status through raw time-lapse video.

Eliminating Indefiniteness of Clinical Spectrum for Better Screening COVID-19.

IEEE journal of biomedical and health informatics
The coronavirus disease 2019 (COVID-19) has swept all over the world. Due to the limited detection facilities, especially in developing countries, a large number of suspected cases can only receive common clinical diagnosis rather than more effective...

Development and validation of MRI-based deep learning models for prediction of microsatellite instability in rectal cancer.

Cancer medicine
BACKGROUND: Microsatellite instability (MSI) predetermines responses to adjuvant 5-fluorouracil and immunotherapy in rectal cancer and serves as a prognostic biomarker for clinical outcomes. Our objective was to develop and validate a deep learning m...

ai-corona: Radiologist-assistant deep learning framework for COVID-19 diagnosis in chest CT scans.

PloS one
The development of medical assisting tools based on artificial intelligence advances is essential in the global fight against COVID-19 outbreak and the future of medical systems. In this study, we introduce ai-corona, a radiologist-assistant deep lea...

The Comprehensive Machine Learning Analytics for Heart Failure.

International journal of environmental research and public health
: Early detection of heart failure is the basis for better medical treatment and prognosis. Over the last decades, both prevalence and incidence rates of heart failure have increased worldwide, resulting in a significant global public health issue. H...

Application of machine learning in predicting hospital readmissions: a scoping review of the literature.

BMC medical research methodology
BACKGROUND: Advances in machine learning (ML) provide great opportunities in the prediction of hospital readmission. This review synthesizes the literature on ML methods and their performance for predicting hospital readmission in the US.

Domain adaptation and self-supervised learning for surgical margin detection.

International journal of computer assisted radiology and surgery
PURPOSE: One in five women who undergo breast conserving surgery will need a second revision surgery due to remaining tumor. The iKnife is a mass spectrometry modality that produces real-time margin information based on the metabolite signatures in s...

Clinical use of machine learning-based pathomics signature for diagnosis and survival prediction of bladder cancer.

Cancer science
Traditional histopathology performed by pathologists by the naked eye is insufficient for accurate and efficient diagnosis of bladder cancer (BCa). We collected 643 H&E-stained BCa images from Shanghai General Hospital and The Cancer Genome Atlas (TC...