@article{nokey,

title = {AI \& COVID-19},

author = {Davide Bacciu and Emanuela Girardi and Marco Maratea and Jose Sousa

},

url = {https://content.iospress.com/download/intelligenza-artificiale/ia210121?id=intelligenza-artificiale%2Fia210121},

doi = {DOI 10.3233/IA-210121},

year  = {2021},

date = {2021-01-21},

journal = {Intelligenza Artificiale},

abstract = {The COVID-19 pandemic has influenced our lives significantly since March 2020, and a number of initiatives have

been put forward in order to tackle its effects, including those focused on technological solutions. In this paper, we present

one of such initiatives, i.e. the CLAIRE’s taskforce on AI and COVID-19, in which Artificial Intelligence methodologies and

tools are being developed to help the society contrasting the pandemic. We present the different lines of development within

the taskforce, some fields in which they are used, and draw few recommendations},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{sitek2021artificial,

title = {Artificial Intelligence in PET: an Industry Perspective},

author = {Arkadiusz Sitek and Sangtae Ahn and Evren Asma and Adam Chandler and Alvin Ihsani and Sven Prevrhal and Arman Rahmim and Babak Saboury and Kris Thielemans},

url = {https://arxiv.org/abs/2107.06747},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {PET Clinics},

abstract = {Artificial intelligence (AI) has significant potential to positively impact and advance medical imaging, including positron emission tomography (PET) imaging applications. AI has the ability to enhance and optimize all aspects of the PET imaging chain from patient scheduling, patient setup, protocoling, data acquisition, detector signal processing, reconstruction, image processing and interpretation. AI poses industry-specific challenges which will need to be addressed and overcome to maximize the future potentials of AI in PET. This paper provides an overview of these industry-specific challenges for the development, standardization, commercialization, and clinical adoption of AI, and explores the potential enhancements to PET imaging brought on by AI in the near future. In particular, the combination of on-demand image reconstruction, AI, and custom designed data processing workflows may open new possibilities for innovation which would positively impact the industry and ultimately patients.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Malawski2017,

title = {Serverless execution of scientific workflows: Experiments with HyperFlow, AWS Lambda and Google Cloud Functions},

author = {Maciej Malawski and Adam Gajek and Adam Zima and Bartosz Balis and Kamil Figiela},

url = {http://linkinghub.elsevier.com/retrieve/pii/S0167739X1730047X https://linkinghub.elsevier.com/retrieve/pii/S0167739X1730047X},

doi = {10.1016/j.future.2017.10.029},

issn = {0167739X},

year  = {2020},

date = {2020-09-01},

urldate = {2020-09-01},

journal = {Future Generation Computer Systems},

volume = {110},

pages = {502--514},

abstract = {Scientific workflows consisting of a high number of interdependent tasks represent an important class of complex scientific applications. Recently, a new type of serverless infrastructures has emerged, represented by such services as Google Cloud Functions and AWS Lambda, also referred to as the Function-as-a-Service model. In this paper we take a look at such serverless infrastructures, which are designed mainly for processing background tasks of Web and Internet of Things applications, or event-driven stream processing. We evaluate their applicability to more compute- and data-intensive scientific workflows and discuss possible ways to repurpose serverless architectures for execution of scientific workflows. We have developed prototype workflow executor functions using AWS Lambda and Google Cloud Functions, coupled with the HyperFlow workflow engine. These functions can run workflow tasks in AWS and Google infrastructures, and feature such capabilities as data staging to/from S3 or Google Cloud Storage and execution of custom application binaries. We have successfully deployed and executed the Montage astronomy workflow, often used as a benchmark, and we report on initial results of its performance evaluation. Our findings indicate that the simple mode of operation makes this approach easy to use, although there are costs involved in preparing portable application binaries for execution in a remote environment.While our solution is an early prototype, we find the presented approach highly promising. We also discuss possible future steps related to execution of scientific workflows in serverless infrastructures. Finally, we perform a cost analysis and discuss implications with regard to resource management for scientific applications in general.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Sitek2021,

title = {Genome-Wide Association Study of Brain Connectivity Changes for Alzheimer’s Disease},

author = {Alessandro Crimi and Nicola J. Mulder and Emile R. Chimusa and Samar S. M. Elsheikh









},

doi = {https://doi.org/10.1038/s41598-020-58291-1},

year  = {2020},

date = {2020-01-29},

urldate = {2020-01-29},

abstract = {Variations in the human genome have been found to be an essential factor that affects susceptibility to Alzheimer’s disease. Genome-wide association studies (GWAS) have identified genetic loci that significantly contribute to the risk of Alzheimers. The availability of genetic data, coupled with brain imaging technologies have opened the door for further discoveries, by using data integration methodologies and new study designs. Although methods have been proposed for integrating image characteristics and genetic information for studying Alzheimers, the measurement of disease is often taken at a single time point, therefore, not allowing the disease progression to be taken into consideration. In longitudinal settings, we analyzed neuroimaging and single nucleotide polymorphism datasets obtained from the Alzheimer’s Disease Neuroimaging Initiative for three clinical stages of the disease, including healthy control, early mild cognitive impairment and Alzheimer’s disease subjects. We conducted a GWAS regressing the absolute change of global connectivity metrics on the genetic variants, and used the GWAS summary statistics to compute the gene and pathway scores. We observed significant associations between the change in structural brain connectivity defined by tractography and genes, which have previously been reported to biologically manipulate the risk and progression of certain neurodegenerative disorders, including Alzheimer’s disease.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Nowakowski2018,

title = {Cloud computing infrastructure for the VPH community},

author = {Piotr Nowakowski and Marian Bubak and Tomasz Barty\'{n}ski and Tomasz Guba\la and Daniel Harce\.{z}lak and Marek Kasztelnik and Maciej Malawski and Jan Meizner},

doi = {10.1016/j.jocs.2017.06.012},

issn = {18777503},

year  = {2018},

date = {2018-01-01},

urldate = {2018-01-01},

journal = {Journal of Computational Science},

volume = {24},

pages = {169--179},

publisher = {Elsevier B.V.},

abstract = {As virtualization technologies mature and become ever more widespread, cloud computing has emerged as a promising paradigm for e-science. In order to facilitate successful application of cloud computing in scientific research \textendash particularly in a domain as security-minded as medical research \textendash several technical challenges need to be addressed. This paper reports on the successful deployment and utilization of a cloud computing platform for the Virtual Physiological Human (VPH) research community, originating in the VPH-Share project and continuing beyond the end of this project. The platform tackles technical issues involved in porting existing desktop applications to the cloud environment and constitutes a uniform research space where application services can be developed, stored, accessed and shared using a variety of computational infrastructures. The paper also presents examples of application workflows which make use of the presented infrastructure \textendash both internal and external to the VPH community.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Amoah2016,

title = {Boosting antenatal care attendance and number of hospital deliveries among pregnant women in rural communities: a community initiative in Ghana based on mobile phones applications and portable ultrasound scans},

author = {Benjamin Amoah and Evelyn A. Anto and Prince K. Osei and Kojo Pieterson and Alessandro Crimi},

url = {https://rdcu.be/cxfpM},

doi = {https://doi.org/10.1186/s12884-016-0888-x},

year  = {2016},

date = {2016-06-14},

urldate = {2016-06-14},

abstract = {The World Health Organization has recommended at least four antenatal care (ANC) visits and skilled attendants at birth. Most pregnant women in rural communities in low-income countries do not achieve the minimum recommended visits and deliver without skilled attendants. With the aim of increasing number of ANC visits, reducing home deliveries, and supplementing care given by ANC clinics, a proposed system based on low-cost mobile phones and portable ultrasound scan machines was piloted.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}