AIMC Topic: Algorithms

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CUP-AI-Dx: A tool for inferring cancer tissue of origin and molecular subtype using RNA gene-expression data and artificial intelligence.

EBioMedicine
BACKGROUND: Cancer of unknown primary (CUP), representing approximately 3-5% of all malignancies, is defined as metastatic cancer where a primary site of origin cannot be found despite a standard diagnostic workup. Because knowledge of a patient's pr...

Robust deep learning classification of adamantinomatous craniopharyngioma from limited preoperative radiographic images.

Scientific reports
Deep learning (DL) is a widely applied mathematical modeling technique. Classically, DL models utilize large volumes of training data, which are not available in many healthcare contexts. For patients with brain tumors, non-invasive diagnosis would r...

Myoelectric digit action decoding with multi-output, multi-class classification: an offline analysis.

Scientific reports
The ultimate goal of machine learning-based myoelectric control is simultaneous and independent control of multiple degrees of freedom (DOFs), including wrist and digit artificial joints. For prosthetic finger control, regression-based methods are ty...

Evaluation of a genetic risk score for severity of COVID-19 using human chromosomal-scale length variation.

Human genomics
INTRODUCTION: The course of COVID-19 varies from asymptomatic to severe in patients. The basis for this range in symptoms is unknown. One possibility is that genetic variation is partly responsible for the highly variable response. We evaluated how w...

Computer-aided recognition of myopic tilted optic disc using deep learning algorithms in fundus photography.

BMC ophthalmology
BACKGROUND: It is necessary to consider myopic optic disc tilt as it seriously impacts normal ocular parameters. However, ophthalmologic measurements are within inter-observer variability and time-consuming to get. This study aimed to develop and eva...

Advancements in sex estimation using the diaphyseal cross-sectional geometric properties of the lower and upper limbs.

International journal of legal medicine
This paper introduces an automated method for estimating sex from the lower and upper limbs based on diaphyseal CSG properties. The proposed method was developed and evaluated using 389 femurs, 412 tibias, and 404 humeri of adult individuals from a m...

Neural network-based model predictive tracking control of an uncertain robotic manipulator with input constraints.

ISA transactions
This paper proposes a neural network-based model predictive control (MPC) method for robotic manipulators with model uncertainty and input constraints. In the presented NN-based MPC structure, two groups of radial basis function neural networks (RBFN...

Extravalidation and reproducibility results of a commercial deep learning-based automatic detection algorithm for pulmonary nodules on chest radiographs at tertiary hospital.

Journal of medical imaging and radiation oncology
INTRODUCTION: To extra validate and evaluate the reproducibility of a commercial deep convolutional neural network (DCNN) algorithm for pulmonary nodules on chest radiographs (CRs) and to compare its performance with radiologists.

PAIP 2019: Liver cancer segmentation challenge.

Medical image analysis
Pathology Artificial Intelligence Platform (PAIP) is a free research platform in support of pathological artificial intelligence (AI). The main goal of the platform is to construct a high-quality pathology learning data set that will allow greater ac...

Development and validation of a deep learning algorithm for auto-delineation of clinical target volume and organs at risk in cervical cancer radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: The delineation of the clinical target volume (CTV) is a crucial, laborious and subjective step in cervical cancer radiotherapy. The aim of this study was to propose and evaluate a novel end-to-end convolutional neural network (CNN) for full...