Browsing by Subject "artificial intelligence"
Now showing items 1-20 of 22
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5G and human health
(2021)The considerable characteristics of 5G technology (Fifth Generation of telecommunication) is the very high amount of data that can be transmitted in the time unit (data speed: Megabits per second - throughput) and the very ... -
Are computational applications the “crystal ball” in the IVF laboratory? The evolution from mathematics to artificial intelligence
(2018)Mathematics rules the world of science. Innovative technologies based on mathematics have paved the way for implementation of novel strategies in assisted reproduction. Ascertaining efficient embryo selection in order to ... -
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Artificial Intelligence in Cardiology—A Narrative Review of Current Status
(2022)Artificial intelligence (AI) is an integral part of clinical decision support systems (CDSS), offering methods to approximate human reasoning and computationally infer decisions. Such methods are generally based on medical ... -
Artificial intelligence in small bowel capsule endoscopy - current status, challenges and future promise
(2021)Neural network-based solutions are under development to alleviate physicians from the tedious task of small-bowel capsule endoscopy reviewing. Computer-assisted detection is a critical step, aiming to reduce reading times ... -
Big Data in Laboratory Medicine—FAIR Quality for AI?
(2022)Laboratory medicine is a digital science. Every large hospital produces a wealth of data each day—from simple numerical results from, e.g., sodium measurements to highly complex output of “-omics” analyses, as well as ... -
COVID-19 Phenotypes and Comorbidity: A Data-Driven, Pattern Recognition Approach Using National Representative Data from the United States
(2022)The aim of our study was to determine COVID-19 syndromic phenotypes in a data-driven manner using the survey results based on survey results from Carnegie Mellon University’s Delphi Group. Monthly survey results (>1 million ... -
Current Trends of Computational Tools in Geriatric Medicine and Frailty Management
(2022)While frailty corresponds to a multisystem failure, geriatric assessment can recognize multiple pathophysiological lesions and age changes. Up to now, a few frailty indexes have been introduced, presenting definitions of ... -
Design Space Exploration of a Sparse MobileNetV2 Using High-Level Synthesis and Sparse Matrix Techniques on FPGAs
(2022)Convolution Neural Networks (CNNs) are gaining ground in deep learning and Artificial Intelligence (AI) domains, and they can benefit from rapid prototyping in order to produce efficient and low-power hardware designs. The ... -
Differentiation between subchondral insufficiency fractures and advanced osteoarthritis of the knee using transfer learning and an ensemble of convolutional neural networks
(2022)Purpose: Subchondral insufficiency fractures (SIF) and advanced osteoarthritis (OA) of the knee are usually seen in conjunction with bone marrow lesions (BMLs) and their differentiation may pose a significant diagnostic ... -
ERS International Congress 2021: highlights from the Thoracic Surgery and Lung Transplantation Assembly
(2022)The thoracic surgery and lung transplantation assembly of the European Respiratory Society (ERS) is delighted to present the highlights from the 2021 ERS International Congress. We have selected four sessions that discussed ... -
An Explainable Machine Learning Pipeline for Stroke Prediction on Imbalanced Data
(2022)Stroke is an acute neurological dysfunction attributed to a focal injury of the central nervous system due to reduced blood flow to the brain. Nowadays, stroke is a global threat associated with premature death and huge ... -
Key research questions for implementation of artificial intelligence in capsule endoscopy
(2022)Background: Artificial intelligence (AI) is rapidly infiltrating multiple areas in medicine, with gastrointestinal endoscopy paving the way in both research and clinical applications. Multiple challenges associated with ... -
Land-use planning via enhanced multi-objective evolutionary algorithms: optimizing the land value of major Greenfield initiatives
(2016)The successful implementation of major development initiatives relies on the sound allocation of land uses against critical design criteria and constraints. The discovery of optimum development plans introduces severe ... -
Locational planning for emergency management and response: An artificial intelligence approach
(2012)The efficiency of emergency service systems is measured in terms of their ability to deploy units and personnel in a timely and effective manner upon an event's occurrence. When dealing with public sector institutions, ... -
Minutely active power forecasting models using neural networks
(2020)Power forecasting is an integral part of the Demand Response design philosophy for power systems, enabling utility companies to understand the electricity consumption patterns of their customers and adjust price signals ... -
Modelling of infiltration using artificial intelligence techniques in semi-arid Iran
(2019)Infiltration plays a fundamental role in streamflow, groundwater recharge, subsurface flow, and surface and subsurface water quality and quantity. In this study, adaptive neuro-fuzzy inference system (ANFIS), support vector ... -
Multilayer Feed Forward Models in Groundwater Level Forecasting Using Meteorological Data in Public Management
(2018)Managing the groundwater resources is very vital for human life. This research proposes a methodology for predicting the groundwater levels which can be very valuable in water resources management. This study investigates ... -
PCaGuard: A Software Platform to Support Optimal Management of Prostate Cancer
(2021)Background and Objective Prostate cancer (PCa) is a severe public health issue and the most common cancer worldwide in men. Early diagnosis can lead to early treatment and long-term survival. The addition of the multiparametric ... -
Position paper of the EACVI and EANM on artificial intelligence applications in multimodality cardiovascular imaging using SPECT/CT, PET/CT, and cardiac CT
(2021)In daily clinical practice, clinicians integrate available data to ascertain the diagnostic and prognostic probability of a disease or clinical outcome for their patients. For patients with suspected or known cardiovascular ...