AIMC Topic: Humans

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A deep learning model based on whole slide images to predict disease-free survival in cutaneous melanoma patients.

Scientific reports
The application of deep learning on whole-slide histological images (WSIs) can reveal insights for clinical and basic tumor science investigations. Finding quantitative imaging biomarkers from WSIs directly for the prediction of disease-free survival...

Artificial intelligence to understand fluctuation of fetal brain activity by recognizing facial expressions.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: To examine whether artificial intelligence can achieve discoveries regarding fetal brain activity.

Prognostic features of upstaged pT3a renal tumors with fat invasion after robot-assisted partial nephrectomy: is it time for a new subclassification?

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
INTRODUCTION: The clinical management of pT3a pathologic-upstaged renal cell carcinoma (RCC) patients is actually controversial. Aim of this study was i) to assess the impact of pT3a upstaging on oncologic outcomes after robot-assisted partial nephre...

Integrative transcriptome analysis of SARS-CoV-2 human-infected cells combined with deep learning algorithms identifies two potential cellular targets for the treatment of coronavirus disease.

Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology]
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) quickly spread worldwide, leading coronavirus disease 2019 (COVID-19) to hit pandemic level less than 4 months after the first official cases. Hence, the search for drugs and vaccines that ...

The right to a second opinion on Artificial Intelligence diagnosis-Remedying the inadequacy of a risk-based regulation.

Bioethics
In this paper, we argue that patients who are subjects of Artificial Intelligence (AI)-supported diagnosis and treatment planning should have a right to a second opinion, but also that this right should not necessarily be construed as a right to a ph...

Technical note: Phantom-based training framework for convolutional neural network CT noise reduction.

Medical physics
BACKGROUND: Deep artificial neural networks such as convolutional neural networks (CNNs) have been shown to be effective models for reducing noise in CT images while preserving anatomic details. A practical bottleneck for developing CNN-based denoisi...

Improved accuracy of auto-segmentation of organs at risk in radiotherapy planning for nasopharyngeal carcinoma based on fully convolutional neural network deep learning.

Oral oncology
OBJECTIVE: We examined a modified encoder-decoder architecture-based fully convolutional neural network, OrganNet, for simultaneous auto-segmentation of 24 organs at risk (OARs) in the head and neck, followed by validation tests and evaluation of cli...