AIMC Topic: Area Under Curve

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Deep learning radiomics of ultrasonography for differentiating sclerosing adenosis from breast cancer.

Clinical hemorheology and microcirculation
OBJECTIVES: The purpose of our study is to present a method combining radiomics with deep learning and clinical data for improved differential diagnosis of sclerosing adenosis (SA)and breast cancer (BC).

Estimation of Mycophenolic Acid Exposure in Chinese Renal Transplant Patients by a Joint Deep Learning Model.

Therapeutic drug monitoring
BACKGROUND: To predict mycophenolic acid (MPA) exposure in renal transplant recipients using a deep learning model based on a convolutional neural network with bilateral long short-term memory and attention methods.

IIFDTI: predicting drug-target interactions through interactive and independent features based on attention mechanism.

Bioinformatics (Oxford, England)
MOTIVATION: Identifying drug-target interactions is a crucial step for drug discovery and design. Traditional biochemical experiments are credible to accurately validate drug-target interactions. However, they are also extremely laborious, time-consu...

Using Explainable Artificial Intelligence Models (ML) to Predict Suspected Diagnoses as Clinical Decision Support.

Studies in health technology and informatics
The complexity of emergency cases and the number of emergency patients have increased dramatically. Due to a reduced or even missing specialist medical staff in the emergency departments (EDs), medical knowledge is often used without professional sup...

Deep Learning for Discrimination Between Fungal Keratitis and Bacterial Keratitis: DeepKeratitis.

Cornea
PURPOSE: Microbial keratitis is an urgent condition in ophthalmology that requires prompt treatment. This study aimed to apply deep learning algorithms for rapidly discriminating between fungal keratitis (FK) and bacterial keratitis (BK).

Lens Opacities Classification System III-based artificial intelligence program for automatic cataract grading.

Journal of cataract and refractive surgery
PURPOSE: To establish and validate an artificial intelligence (AI)-assisted automatic cataract grading program based on the Lens Opacities Classification System III (LOCS III).

Resampling to address inequities in predictive modeling of suicide deaths.

BMJ health & care informatics
OBJECTIVE: Improve methodology for equitable suicide death prediction when using sensitive predictors, such as race/ethnicity, for machine learning and statistical methods.

Deep Convolutional Neural Networks Implementation for the Analysis of Urine Culture.

Clinical chemistry
BACKGROUND: Urine culture images collected using bacteriology automation are currently interpreted by technologists during routine standard-of-care workflows. Machine learning may be able to improve the harmonization of and assist with these interpre...

Multi-variable AUC for sifting complementary features and its biomedical application.

Briefings in bioinformatics
Although sifting functional genes has been discussed for years, traditional selection methods tend to be ineffective in capturing potential specific genes. First, typical methods focus on finding features (genes) relevant to class while irrelevant to...

Potential for Process Improvement of Clinical Flow Cytometry by Incorporating Real-Time Automated Screening of Data to Expedite Addition of Antibody Panels.

American journal of clinical pathology
OBJECTIVES: We desired an automated approach to expedite ordering additional antibody panels in our clinical flow cytometry lab. This addition could improve turnaround times, decrease time spent revisiting cases, and improve consistency.