AIMC Topic: ROC Curve

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Explaining the Rationale of Deep Learning Glaucoma Decisions with Adversarial Examples.

Ophthalmology
PURPOSE: To illustrate what is inside the so-called black box of deep learning models (DLMs) so that clinicians can have greater confidence in the conclusions of artificial intelligence by evaluating adversarial explanation on its ability to explain ...

Truncated inception net: COVID-19 outbreak screening using chest X-rays.

Physical and engineering sciences in medicine
Since December 2019, the Coronavirus Disease (COVID-19) pandemic has caused world-wide turmoil in a short period of time, and the infection, caused by SARS-CoV-2, is spreading rapidly. AI-driven tools are used to identify Coronavirus outbreaks as wel...

Single-Cell Classification Using Mass Spectrometry through Interpretable Machine Learning.

Analytical chemistry
The brain consists of organized ensembles of cells that exhibit distinct morphologies, cellular connectivity, and dynamic biochemistries that control the executive functions of an organism. However, the relationships between chemical heterogeneity, c...

Serum markers improve current prediction of metastasis development in early-stage melanoma patients: a machine learning-based study.

Molecular oncology
Metastasis development represents an important threat for melanoma patients, even when diagnosed at early stages and upon removal of the primary tumor. In this scenario, determination of prognostic biomarkers would be of great interest. Serum contain...

From Local to Global: A Graph Framework for Retinal Artery/Vein Classification.

IEEE transactions on nanobioscience
Fundus photography has been widely used for inspecting eye disorders by ophthalmologists or computer algorithms. Biomarkers related to retinal vessels plays an essential role to detect early diabetes. To quantify vascular biomarkers or the correspond...

On-line anxiety level detection from biosignals: Machine learning based on a randomized controlled trial with spider-fearful individuals.

PloS one
We present performance results concerning the validation for anxiety level detection based on trained mathematical models using supervised machine learning techniques. The model training is based on biosignals acquired in a randomized controlled tria...

Clinical-Grade Detection of Microsatellite Instability in Colorectal Tumors by Deep Learning.

Gastroenterology
BACKGROUND & AIMS: Microsatellite instability (MSI) and mismatch-repair deficiency (dMMR) in colorectal tumors are used to select treatment for patients. Deep learning can detect MSI and dMMR in tumor samples on routine histology slides faster and le...

Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population.

International immunopharmacology
Since December 2019 the novel coronavirus SARS-CoV-2 has been identified as the cause of the pandemic COVID-19. Early symptoms overlap with other common conditions such as common cold and Influenza, making early screening and diagnosis are crucial go...