AIMC Topic: Algorithms

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Crowdsourcing airway annotations in chest computed tomography images.

PloS one
Measuring airways in chest computed tomography (CT) scans is important for characterizing diseases such as cystic fibrosis, yet very time-consuming to perform manually. Machine learning algorithms offer an alternative, but need large sets of annotate...

H estimation for stochastic semi-Markovian switching CVNNs with missing measurements and mode-dependent delays.

Neural networks : the official journal of the International Neural Network Society
This article is devoted to the H estimation problem for stochastic semi-Markovian switching complex-valued neural networks subject to incomplete measurement outputs, where the time-varying delay also depends on another semi-Markov process. A sequence...

Multimodal super-resolved q-space deep learning.

Medical image analysis
Super-resolvedq-space deep learning (SR-q-DL) has been developed to estimate high-resolution (HR) tissue microstructure maps from low-quality diffusion magnetic resonance imaging (dMRI) scans acquired with a reduced number of diffusion gradients and ...

Towards markerless surgical tool and hand pose estimation.

International journal of computer assisted radiology and surgery
PURPOSE:  : Tracking of tools and surgical activity is becoming more and more important in the context of computer assisted surgery. In this work, we present a data generation framework, dataset and baseline methods to facilitate further research in ...

Prediction of causative genes in inherited retinal disorder from fundus photography and autofluorescence imaging using deep learning techniques.

The British journal of ophthalmology
BACKGROUND/AIMS: To investigate the utility of a data-driven deep learning approach in patients with inherited retinal disorder (IRD) and to predict the causative genes based on fundus photography and fundus autofluorescence (FAF) imaging.

Living systems are smarter bots: Slime mold semiosis versus AI symbol manipulation.

Bio Systems
Although machines may be good at mimicking, they are not currently able, as organisms are, to act creatively. We offer an understanding of the emergent qualities of biological sign processing in terms of generalization, association, and encryption. W...

Deep learning to detect acute respiratory distress syndrome on chest radiographs: a retrospective study with external validation.

The Lancet. Digital health
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a common, but under-recognised, critical illness syndrome associated with high mortality. An important factor in its under-recognition is the variability in chest radiograph interpretation for...

AutoDTI++: deep unsupervised learning for DTI prediction by autoencoders.

BMC bioinformatics
BACKGROUND: Drug-target interaction (DTI) plays a vital role in drug discovery. Identifying drug-target interactions related to wet-lab experiments are costly, laborious, and time-consuming. Therefore, computational methods to predict drug-target int...

Distinguishing Rectal Cancer from Colon Cancer Based on the Support Vector Machine Method and RNA-sequencing Data.

Current medical science
Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide. Several studies have indicated that rectal cancer is significantly different from colon cancer in terms of treatment, prognosis, and metastasis. Recently, the differential...

Artificial Intelligence-Based Diagnosis of Diabetes Mellitus: Combining Fundus Photography with Traditional Chinese Medicine Diagnostic Methodology.

BioMed research international
In this study, we propose a technique for diagnosing both type 1 and type 2 diabetes in a quick, noninvasive way by using equipment that is easy to transport. Diabetes mellitus is a chronic disease that affects public health globally. Although diabet...