Titlebook: Artificial Intelligence in Health; First International Fernando Koch,Andrew Koster,Nirmalie Wiratunga Conference proceedings 2019 Springer

ANIM

A Knowledge-Based Simulation Framework for Decision Support in Brazilian National Cancer Institutee has been emphasized in the researches to support evidence-based medicine. Currently, cancer is responsible for over 130,000 deaths every year in Brazil. Extensive waiting queues for diagnosis and treatments have become routine. One of the critical success factors in a cancer treatment is the early

魔鬼在游行

Lifted Maximum Expected Utility first-order cluster representation. We extend the underling model representation of LJT, which is called parameterised probabilistic model, to calculate a lifted solution to the maximum expected utility (MEU) problem. Specifically, this paper contributes (i) action and utility nodes for parameteris

abracadabra

營養(yǎng)

Allure

Towards Automated Pain Detection in Children Using Facial and Electrodermal ActivityDA) provide rich information about pain, and both have been used in automated pain detection. In this paper, we discuss preliminary steps towards fusing models trained on video and EDA features respectively. We compare fusion models using original video features and those using transferred video fea

項(xiàng)目

Interpretation of Best Medical Coding Practices by Case-Based Reasoning—A User Assistance Prototype process is ruled by complex international standards and numerous best practices, which can easily overwhelm (coding) operators. In this paper, a system assisting operators in the interpretation of best medical coding practices and a short evaluation are presented. By leveraging the arguments used b

初學(xué)者

胎兒

Generating Reward Functions Using IRL Towards Individualized Cancer Screening advocates the need for more personalized methods. Partially observable Markov decision processes (POMDPs), when defined with an appropriate reward function, can be used to suggest optimal, individualized screening policies. However, determining an appropriate reward function can be challenging. Her

cogitate

Deep Learning Architectures for Vector Representations of Patients and Exploring Predictors of 30-Das the use of deep learning architectures to identify patient segments and contributing factors to 30-day hospital readmissions. We implemented Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) on sequential Electronic Health Records data at the Danderyd Hospital in Stockholm, Swe

contradict

Artificial Intelligence in Health978-3-030-12738-1Series ISSN 0302-9743 Series E-ISSN 1611-3349