AI Medical Compendium Journal:
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Showing 111 to 120 of 148 articles

HunCRC: annotated pathological slides to enhance deep learning applications in colorectal cancer screening.

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Histopathology is the gold standard method for staging and grading human tumors and provides critical information for the oncoteam's decision making. Highly-trained pathologists are needed for careful microscopic analysis of the slides produced from ...

A dataset of simulated patient-physician medical interviews with a focus on respiratory cases.

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Artificial Intelligence (AI) is playing a major role in medical education, diagnosis, and outbreak detection through Natural Language Processing (NLP), machine learning models and deep learning tools. However, in order to train AI to facilitate these...

QMugs, quantum mechanical properties of drug-like molecules.

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Machine learning approaches in drug discovery, as well as in other areas of the chemical sciences, benefit from curated datasets of physical molecular properties. However, there currently is a lack of data collections featuring large bioactive molecu...

Plant phenotype relationship corpus for biomedical relationships between plants and phenotypes.

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Medicinal plants have demonstrated therapeutic potential for applicability for a wide range of observable characteristics in the human body, known as "phenotype," and have been considered favorably in clinical treatment. With an ever increasing inter...

A pediatric wrist trauma X-ray dataset (GRAZPEDWRI-DX) for machine learning.

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Digital radiography is widely available and the standard modality in trauma imaging, often enabling to diagnose pediatric wrist fractures. However, image interpretation requires time-consuming specialized training. Due to astonishing progress in comp...

GEOM, energy-annotated molecular conformations for property prediction and molecular generation.

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Machine learning (ML) outperforms traditional approaches in many molecular design tasks. ML models usually predict molecular properties from a 2D chemical graph or a single 3D structure, but neither of these representations accounts for the ensemble ...

Categorized contrast enhanced mammography dataset for diagnostic and artificial intelligence research.

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Contrast-enhanced spectral mammography (CESM) is a relatively recent imaging modality with increased diagnostic accuracy compared to digital mammography (DM). New deep learning (DL) models were developed that have accuracies equal to that of an avera...

Daily motionless activities: A dataset with accelerometer, magnetometer, gyroscope, environment, and GPS data.

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The dataset presented in this paper presents a dataset related to three motionless activities, including driving, watching TV, and sleeping. During these activities, the mobile device may be positioned in different locations, including the pants pock...

ICEO, a biological ontology for representing and analyzing bacterial integrative and conjugative elements.

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Bacterial integrative and conjugative elements (ICEs) are highly modular mobile genetic elements critical to the horizontal transfer of antibiotic resistance and virulence factor genes. To better understand and analyze the ongoing increase of ICEs, w...

Segmentation of vestibular schwannoma from MRI, an open annotated dataset and baseline algorithm.

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Automatic segmentation of vestibular schwannomas (VS) from magnetic resonance imaging (MRI) could significantly improve clinical workflow and assist patient management. We have previously developed a novel artificial intelligence framework based on a...