AIMC Topic: Area Under Curve

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Comparison of Chest Radiograph Interpretations by Artificial Intelligence Algorithm vs Radiology Residents.

JAMA network open
IMPORTANCE: Chest radiography is the most common diagnostic imaging examination performed in emergency departments (EDs). Augmenting clinicians with automated preliminary read assistants could help expedite their workflows, improve accuracy, and redu...

Advancing predictive modeling in archaeology: An evaluation of regression and machine learning methods on the Grand Staircase-Escalante National Monument.

PloS one
Predictive models are central to both archaeological research and cultural resource management. Yet, archaeological applications of predictive models are often insufficient due to small training data sets, inadequate statistical techniques, and a lac...

Leveraging TCGA gene expression data to build predictive models for cancer drug response.

BMC bioinformatics
BACKGROUND: Machine learning has been utilized to predict cancer drug response from multi-omics data generated from sensitivities of cancer cell lines to different therapeutic compounds. Here, we build machine learning models using gene expression da...

DeeplyEssential: a deep neural network for predicting essential genes in microbes.

BMC bioinformatics
BACKGROUND: Essential genes are those genes that are critical for the survival of an organism. The prediction of essential genes in bacteria can provide targets for the design of novel antibiotic compounds or antimicrobial strategies.

Robust edge-based biomarker discovery improves prediction of breast cancer metastasis.

BMC bioinformatics
BACKGROUND: The abundance of molecular profiling of breast cancer tissues entailed active research on molecular marker-based early diagnosis of metastasis. Recently there is a surging interest in combining gene expression with gene networks such as p...

Assigning the Origin of Microbial Natural Products by Chemical Space Map and Machine Learning.

Biomolecules
Microbial natural products (NPs) are an important source of drugs, however, their structural diversity remains poorly understood. Here we used our recently reported MinHashed Atom Pair fingerprint with diameter of four bonds (MAP4), a fingerprint sui...

Identification of Potential Type II Diabetes in a Large-Scale Chinese Population Using a Systematic Machine Learning Framework.

Journal of diabetes research
BACKGROUND: An estimated 425 million people globally have diabetes, accounting for 12% of the world's health expenditures, and the number continues to grow, placing a huge burden on the healthcare system, especially in those remote, underserved areas...

A machine learning algorithm to increase COVID-19 inpatient diagnostic capacity.

PloS one
Worldwide, testing capacity for SARS-CoV-2 is limited and bottlenecks in the scale up of polymerase chain reaction (PCR-based testing exist. Our aim was to develop and evaluate a machine learning algorithm to diagnose COVID-19 in the inpatient settin...

Influence of medical domain knowledge on deep learning for Alzheimer's disease prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Alzheimer's disease (AD) is the most common type of dementia that can seriously affect a person's ability to perform daily activities. Estimates indicate that AD may rank third as a cause of death for older people, after hea...

Application of machine learning to the prediction of postoperative sepsis after appendectomy.

Surgery
BACKGROUND: We applied various machine learning algorithms to a large national dataset to model the risk of postoperative sepsis after appendectomy to evaluate utility of such methods and identify factors associated with postoperative sepsis in these...