AIMC Topic: Algorithms

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A tree based approach for multi-class classification of surgical procedures using structured and unstructured data.

BMC medical informatics and decision making
BACKGROUND: In surgical department, CPT code assignment has been a complicated manual human effort, that entails significant related knowledge and experience. While there are several studies using CPTs to make predictions in surgical services, litera...

Spliceator: multi-species splice site prediction using convolutional neural networks.

BMC bioinformatics
BACKGROUND: Ab initio prediction of splice sites is an essential step in eukaryotic genome annotation. Recent predictors have exploited Deep Learning algorithms and reliable gene structures from model organisms. However, Deep Learning methods for non...

Assessing the utility of low resolution brain imaging: treatment of infant hydrocephalus.

NeuroImage. Clinical
As low-field MRI technology is being disseminated into clinical settings around the world, it is important to assess the image quality required to properly diagnose and treat a given disease and evaluate the role of machine learning algorithms, such ...

Construction of Financial Management Early Warning Model Based on Improved Ant Colony Neural Network.

Computational intelligence and neuroscience
With the advent of the era of economic globalization, the world capital market is also facing financial risks. It is necessary to have a corresponding financial management early warning model to reduce economic losses. This paper uses the combination...

Scene Text Recognition Based on Bidirectional LSTM and Deep Neural Network.

Computational intelligence and neuroscience
Deep learning is a subfield of artificial intelligence that allows the computer to adopt and learn some new rules. Deep learning algorithms can identify images, objects, observations, texts, and other structures. In recent years, scene text recogniti...

Deep learning-based auto-segmentation of clinical target volumes for radiotherapy treatment of cervical cancer.

Journal of applied clinical medical physics
OBJECTIVES: Because radiotherapy is indispensible for treating cervical cancer, it is critical to accurately and efficiently delineate the radiation targets. We evaluated a deep learning (DL)-based auto-segmentation algorithm for automatic contouring...

Analysis of medical diagnosis based on variation co-efficient similarity measures under picture hesitant fuzzy sets and their application.

Mathematical biosciences and engineering : MBE
One of the most dominant and feasible technique is called the PHF setting is exist in the circumstances of fuzzy set theory for handling intricate and vague data in genuine life scenario. The perception of PHF setting is massive universal is compared...

Fuzzy-interval inequalities for generalized preinvex fuzzy interval valued functions.

Mathematical biosciences and engineering : MBE
In this paper, firstly we define the concept of -preinvex fuzzy-interval-valued functions (-preinvex FIVF). Secondly, some new Hermite-Hadamard type inequalities (- type inequalities) for -preinvex FIVFs via fuzzy integrals are established by means o...

Deep learning-based reconstruction of chest ultra-high-resolution computed tomography and quantitative evaluations of smaller airways.

Respiratory investigation
The full-iterative model reconstruction generates ultra-high-resolution computed tomography (U-HRCT) images comprising a 1024 × 1024 matrix and 0.25 mm thickness while suppressing image noises, allowing evaluating small airways 1-2 mm in diameter. Ho...

Detecting immunotherapy-sensitive subtype in gastric cancer using histologic image-based deep learning.

Scientific reports
Immune checkpoint inhibitor (ICI) therapy is widely used but effective only in a subset of gastric cancers. Epstein-Barr virus (EBV)-positive and microsatellite instability (MSI) / mismatch repair deficient (dMMR) tumors have been reported to be high...