Search results for "Intelligence"
showing 10 items of 6959 documents
A Statistical Study to Analyze the Impact of External Weather Change on Chronic Pulmonary Infection in South Norway with Machine Learning Algorithms
2021
In this paper, we analyzed the holistic impact of external weather on chronic pulmonary infection in the Agder region with traditional machine learning algorithms. Millions of people are diagnosed with Chronic Obstructive Pulmonary Disease (COPD). Our study is dedicated in the Agder region, the Southern part of Norway. Norway has four seasons – winter (December-February), late winter/spring (March-May), Summer (June-August), and Autumn (September-November) in a year with average annual temperature approx. 7.5 °C | 45.5 °F and an annual rainfall of 1260 mm or 49.6 in. in Kristiansand. As predicted by the World Health Organization (WHO), in 2016, Norway suffered from 8% mortality due to c(1)h…
Deep Neural Networks for Prediction of Exacerbations of Patients with Chronic Obstructive Pulmonary Disease
2018
Chronic Obstructive Pulmonary Disease (COPD) patients need help in daily life situations as they are burdened with frequent risks of acute exacerbation and loss of control. An automated monitoring system could lead to timely treatments and avoid unnecessary hospital (re-)admissions and home visits by doctors or nurses. Therefore we present a Deep Artificial Neural Networks for approach prediction of exacerbations, particularly Feed-Forward Neural Networks (FFNN) for classification of COPD patients category and Long Short-Term Memory (LSTM), for early prediction of COPD exacerbations and subsequent triage. The FFNN and LSTM models are trained on data collected from remote monitoring of 94 pa…
Hopelessness and burnout in Italian healthcare workers during COVID-19 pandemic: the mediating role of trait emotional intelligence
2023
Objective: The study aims to assess the impact of COVID-19 on healthcare workers’ work-related stress during the first wave of the pandemic in Italy. The main objective is to investigate the existence of a positive correlation between hopelessness and burnout, assuming that burnout may be a riskfactor for the development of hopelessness, and to analyze the role thattrait Emotional Intelligence (TEI) and changes in workload could have in this relationship. Furthermore, evaluate any significant differences in burnoutand hopelessness levels in the function of some demographic variables, such as gender, professional profiles, and different working zones of Italy, tobetter understand how the di…
Machine learning classification for COVID19 patients performed on small datasets of CT scans.
2022
In this work we evaluated the possibility of carrying out classifications of the outcome of patients with COVID19 disease through machine learning (ML) techniques working on small datasets of computed tomography (CT) images. In fact, one of the most common problems for medical artificial intelligence (AI) applications is the limited availability of annotated clinical data for model training. In the framework of the artificial intelligence in medicine (AIM) project funded by INFN, we analyzed datasets of CT scans of 79 subjects combined with clinical data containing information relating to positive outcome (no need for intensive care) or poor prognosis (admission into intensive care unit and…
3D segmentation of abdominal aorta from CT-scan and MR images
2012
International audience; We designed a generic method for segmenting the aneurismal sac of an abdominal aortic aneurysm (AAA) both from multi-slice MR and CT-scan examinations. It is a semi-automatic method requiring little human intervention and based on graph cut theory to segment the lumen interface and the aortic wall of AAAs. Our segmentation method works independently on MRI and CT-scan volumes and has been tested on a 44 patient dataset and 10 synthetic images. Segmentation and maximum diameter estimation were compared to manual tracing from 4 experts. An inter-observer study was performed in order to measure the variability range of a human observer. Based on three metrics (the maxim…
Cadmium mass measurements between the neutron shell closures at N=50 and 82
2010
International audience; The mass values of the neutron-deficient cadmium isotopes 99−109Cd and of the neutronrich isotopes 114,120,122−124,126,128Cd have been measured using ISOLTRAP. The behavior of the separation energies of the cadmium isotopes from N = 50 to 82 is discussed.
Calibration and Validation
2016
The aim of this chapter is to summarise the problems incurred during the phases of calibrating and validating the extortion racket models used by the GLODERS project. The chapter starts with the discussion of the data availability and summarises shortly the contents of Sect. 4.3. It continues with a discussion of what parameterisation, calibration, sensitivity analysis and validation have to do with each other and ends up with a discussion of the validity of the GLODERS models.
The Use of Artificial Intelligence (AI) in the Radiology Field: What Is the State of Doctor–Patient Communication in Cancer Diagnosis?
2023
Simple Summary Artificial Intelligence (AI) has been increasingly used in radiology to improve diagnostic procedures over the past decades. The application of AI at the time of cancer diagnosis also creates challenges in the way doctors should communicate the use of AI to patients. The present systematic review deals with the patient's psycho-cognitive perspective on AI and the interpersonal skills between patients and physicians when AI is implemented in cancer diagnosis communication. Evidence from the retrieved studies pointed out that the use of AI in radiology is negatively associated with patient trust in AI and patient-centered communication in cancer disease. Background: In the past…
Accelerated T2-Weighted TSE Imaging of the Prostate Using Deep Learning Image Reconstruction: A Prospective Comparison with Standard T2-Weighted TSE …
2021
Multiparametric MRI (mpMRI) of the prostate has become the standard of care in prostate cancer evaluation. Recently, deep learning image reconstruction (DLR) methods have been introduced with promising results regarding scan acceleration. Therefore, the aim of this study was to investigate the impact of deep learning image reconstruction (DLR) in a shortened acquisition process of T2-weighted TSE imaging, regarding the image quality and diagnostic confidence, as well as PI-RADS and T2 scoring, as compared to standard T2 TSE imaging. Sixty patients undergoing 3T mpMRI for the evaluation of prostate cancer were prospectively enrolled in this institutional review board-approved study between O…
SuperHistopath: A Deep Learning Pipeline for Mapping Tumor Heterogeneity on Low-Resolution Whole-Slide Digital Histopathology Images.
2021
High computational cost associated with digital pathology image analysis approaches is a challenge towards their translation in routine pathology clinic. Here, we propose a computationally efficient framework (SuperHistopath), designed to map global context features reflecting the rich tumor morphological heterogeneity. SuperHistopath efficiently combines i) a segmentation approach using the linear iterative clustering (SLIC) superpixels algorithm applied directly on the whole-slide images at low resolution (5x magnification) to adhere to region boundaries and form homogeneous spatial units at tissue-level, followed by ii) classification of superpixels using a convolution neural network (CN…