What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Internal medicine
- Operating system
Marco Aiello spends much of his time researching Web service, World Wide Web, Service, Nuclear medicine and Complex network.
His Web service research incorporates elements of Business process, Mobile computing, Reuse and Information system.
His Service research is multidisciplinary, incorporating elements of Ubiquitous computing, Aggregate, Face and Architecture framework.
His research integrates issues of Radiology and Fractional anisotropy, Diffusion MRI, White matter in his study of Nuclear medicine.
His Complex network study incorporates themes from Distributed generation, Electric power distribution and Topology.
His Electric power distribution research includes themes of Management science, Relevance, Network simulation, TRACE and Complex system.
His most cited work include:
- Energy intelligent buildings based on user activity: A survey (461 citations)
- The Power Grid as a Complex Network: a Survey (422 citations)
- Handbook of Spatial Logics (250 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are World Wide Web, Web service, Artificial intelligence, Software engineering and Internal medicine.
He performs integrative study on World Wide Web and Universal Description Discovery and Integration.
His Web service research incorporates themes from XML, Service and Service.
His study in Business process extends to Service with its themes.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning, Pattern recognition and Natural language processing.
His studies deal with areas such as Oncology and Cardiology as well as Internal medicine.
He most often published in these fields:
- World Wide Web (12.11%)
- Web service (11.14%)
- Artificial intelligence (9.44%)
What were the highlights of his more recent work (between 2018-2021)?
- Internal medicine (7.26%)
- Context (6.54%)
- Magnetic resonance imaging (5.33%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Internal medicine, Context, Magnetic resonance imaging, Environmental economics and Renewable energy.
His Internal medicine study incorporates themes from Oncology and Cardiology.
The concepts of his Magnetic resonance imaging study are interwoven with issues in Positron emission tomography and Neuroscience.
In his research on the topic of Environmental economics, Distributed generation is strongly related with Energy management.
The study incorporates disciplines such as Energy management system and Smart grid in addition to Renewable energy.
He undertakes interdisciplinary study in the fields of Smart grid and Work through his works.
Between 2018 and 2021, his most popular works were:
- Bringing radiomics into a multi-omics framework for a comprehensive genotype–phenotype characterization of oncological diseases (21 citations)
- Patients Selection for Immunotherapy in Solid Tumors: Overcome the Naïve Vision of a Single Biomarker. (21 citations)
- A critical evaluation of glucocorticoids in the management of severe COVID-19. (20 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Internal medicine
- Operating system
His primary scientific interests are in Context, Positron emission tomography, Magnetic resonance imaging, Artificial intelligence and Internal medicine.
His research integrates issues of Frame, Field, Test data generation and Big data in his study of Context.
His Positron emission tomography study introduces a deeper knowledge of Neuroscience.
His Magnetic resonance imaging research incorporates themes from Fabry disease and Biomedical engineering.
His studies in Artificial intelligence integrate themes in fields like Consciousness, Machine learning and Ising model.
He has included themes like Melanoma and Cardiology in his Internal medicine study.
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