AIMC Topic: Humans

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Prognostic prediction of carcinoma by a differential-regulatory-network-embedded deep neural network.

Computational biology and chemistry
The accurate prognostic prediction is essential for precise diagnosis and treatment of carcinoma. In addition to clinical survival prediction method, many computational methods based on transcriptomic data have been proposed to build the prediction m...

Automatic T Staging Using Weakly Supervised Deep Learning for Nasopharyngeal Carcinoma on MR Images.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Recent studies have shown that deep learning can help tumor staging automatically. However, automatic nasopharyngeal carcinoma (NPC) staging is difficult due to the lack of large and slice-level annotated datasets.

ResOT: Resource-Efficient Oblique Trees for Neural Signal Classification.

IEEE transactions on biomedical circuits and systems
Classifiers that can be implemented on chip with minimal computational and memory resources are essential for edge computing in emerging applications such as medical and IoT devices. This paper introduces a machine learning model based on oblique dec...

Object extraction via deep learning-based marker-free tracking framework of surgical instruments for laparoscope-holder robots.

International journal of computer assisted radiology and surgery
PURPOSE: The surgical instrument tracking framework, especially the marker-free surgical instrument tracking framework, is the key to visual servoing which is applied to achieve active control for laparoscope-holder robots. This paper presented a mar...

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...

Hybrid adversarial-discriminative network for leukocyte classification in leukemia.

Medical physics
PURPOSE: Leukemia is a lethal disease that is harmful to bone marrow and overall blood health. The classification of white blood cell images is crucial for leukemia diagnosis. The purpose of this study is to classify white blood cells by extracting d...

IConMHC: a deep learning convolutional neural network model to predict peptide and MHC-I binding affinity.

Immunogenetics
Tumor-specific neoantigens are mutated self-peptides presented by tumor cell major histocompatibility complex (MHC) molecules and are necessary to elicit host's anti-cancer cytotoxic T cell responses. It could be specifically recognized by neoantigen...

Artificial Neural Network for Atrial Fibrillation Identification in Portable Devices.

Sensors (Basel, Switzerland)
Atrial fibrillation (AF) is a common cardiac disorder that can cause severe complications. AF diagnosis is typically based on the electrocardiogram (ECG) evaluation in hospitals or in clinical facilities. The aim of the present work is to propose a n...

Artificial intelligence in health care: laying the Foundation for Responsible, sustainable, and inclusive innovation in low- and middle-income countries.

Globalization and health
The World Health Organization and other institutions are considering Artificial Intelligence (AI) as a technology that can potentially address some health system gaps, especially the reduction of global health inequalities in low- and middle-income c...