AIMC Topic: Algorithms

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Deep-learning-assisted automatic digitization of applicators in 3D CT image-based high-dose-rate brachytherapy of gynecological cancer.

Brachytherapy
PURPOSE: Applicator digitization is one of the most critical steps in 3D high-dose-rate brachytherapy (HDRBT) treatment planning. Motivated by recent advances in deep-learning, we propose a deep-learning-assisted applicator digitization method for 3D...

Intracortical neural activity distal to seizure-onset-areas predicts human focal seizures.

PloS one
The apparent unpredictability of epileptic seizures has a major impact in the quality of life of people with pharmacologically resistant seizures. Here, we present initial results and a proof-of-concept of how focal seizures can be predicted early in...

A Novel Approach for Multi-Lead ECG Classification Using DL-CCANet and TL-CCANet.

Sensors (Basel, Switzerland)
Cardiovascular disease (CVD) has become one of the most serious diseases that threaten human health. Over the past decades, over 150 million humans have died of CVDs. Hence, timely prediction of CVDs is especially important. Currently, deep learning ...

IoT with cloud based lung cancer diagnosis model using optimal support vector machine.

Health care management science
In the last decade, exponential growth of Internet of Things (IoT) and cloud computing takes the healthcare services to the next level. At the same time, lung cancer is identified as a dangerous disease which increases the global mortality rate annua...

Region Extraction and Classification of Skin Cancer: A Heterogeneous framework of Deep CNN Features Fusion and Reduction.

Journal of medical systems
Cancer is one of the leading causes of deaths in the last two decades. It is either diagnosed malignant or benign - depending upon the severity of the infection and the current stage. The conventional methods require a detailed physical inspection by...

Reducing the Hausdorff Distance in Medical Image Segmentation With Convolutional Neural Networks.

IEEE transactions on medical imaging
The Hausdorff Distance (HD) is widely used in evaluating medical image segmentation methods. However, the existing segmentation methods do not attempt to reduce HD directly. In this paper, we present novel loss functions for training convolutional ne...

Finding Needles in a Haystack: Determining Key Molecular Descriptors Associated with the Blood-brain Barrier Entry of Chemical Compounds Using Machine Learning.

Molecular informatics
In this paper we used two sets of calculated molecular descriptors to predict blood-brain barrier (BBB) entry of a collection of 415 chemicals. The set of 579 descriptors were calculated by Schrodinger and TopoCluj software. Polly and Triplet softwar...

AULD: Large Scale Suspicious DNS Activities Detection via Unsupervised Learning in Advanced Persistent Threats.

Sensors (Basel, Switzerland)
In recent years, sensors in the Internet of things have been commonly used in Human's life. APT (Advanced Persistent Threats) has caused serious damage to network security and the sensors play an important role in the attack process. For a long time,...

Machine Learning Approaches for Automated Lesion Detection in Microwave Breast Imaging Clinical Data.

Scientific reports
Breast lesion detection employing state of the art microwave systems provide a safe, non-ionizing technique that can differentiate healthy and non-healthy tissues by exploiting their dielectric properties. In this paper, a microwave apparatus for bre...