AIMC Topic: Algorithms

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Automated Stoichiometry Analysis of Single-Molecule Fluorescence Imaging Traces via Deep Learning.

Journal of the American Chemical Society
The stoichiometry of protein complexes is precisely regulated in cells and is fundamental to protein function. Singe-molecule fluorescence imaging based photobleaching event counting is a new approach for protein stoichiometry determination under phy...

Efficient Deep Network Architectures for Fast Chest X-Ray Tuberculosis Screening and Visualization.

Scientific reports
Automated diagnosis of tuberculosis (TB) from chest X-Rays (CXR) has been tackled with either hand-crafted algorithms or machine learning approaches such as support vector machines (SVMs) and convolutional neural networks (CNNs). Most deep neural net...

Toward an Expert Level of Lung Cancer Detection and Classification Using a Deep Convolutional Neural Network.

The oncologist
BACKGROUND: Computed tomography (CT) is essential for pulmonary nodule detection in diagnosing lung cancer. As deep learning algorithms have recently been regarded as a promising technique in medical fields, we attempt to integrate a well-trained dee...

A novel ECG signal compression method using spindle convolutional auto-encoder.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: With rapid development of telehealth system and cloud platform, traditional 12-ECG signals with high resolution generate heavy burdens in data storage and transmission. This problem is increasingly addressed with various EC...

Interactive biomedical ontology matching.

PloS one
Due to continuous evolution of biomedical data, biomedical ontologies are becoming larger and more complex, which leads to the existence of many overlapping information. To support semantic inter-operability between ontology-based biomedical systems,...

Deep Robust Framework for Protein Function Prediction Using Variable-Length Protein Sequences.

IEEE/ACM transactions on computational biology and bioinformatics
The order of amino acids in a protein sequence enables the protein to acquire a conformation suitable for performing functions, thereby motivating the need to analyze these sequences for predicting functions. Although machine learning based approache...

Deep Q Learning Driven CT Pancreas Segmentation With Geometry-Aware U-Net.

IEEE transactions on medical imaging
The segmentation of pancreas is important for medical image analysis, yet it faces great challenges of class imbalance, background distractions, and non-rigid geometrical features. To address these difficulties, we introduce a deep Q network (DQN) dr...

A Roadmap for Foundational Research on Artificial Intelligence in Medical Imaging: From the 2018 NIH/RSNA/ACR/The Academy Workshop.

Radiology
Imaging research laboratories are rapidly creating machine learning systems that achieve expert human performance using open-source methods and tools. These artificial intelligence systems are being developed to improve medical image reconstruction, ...

Monitoring the level of hypnosis using a hierarchical SVM system.

Journal of clinical monitoring and computing
Monitoring level of hypnosis is a major ongoing challenge for anesthetists to reduce anesthetic drug consumption, avoiding intraoperative awareness and prolonged recovery. This paper proposes a novel automated method for accurate assessing of the lev...

Deep learning and manual assessment show that the absolute mitotic count does not contain prognostic information in triple negative breast cancer.

Cellular oncology (Dordrecht, Netherlands)
PURPOSE: The prognostic value of mitotic count for invasive breast cancer is firmly established. As yet, however, limited studies have been aimed at assessing mitotic counts as a prognostic factor for triple negative breast cancers (TNBC). Here, we a...