A Review on the use of Artificial Intelligence Techniques in Brain MRI Analysis

Over the past 20 years, the global research going on in Artificial Intelligence in applica-tions in medication is a venue internationally, for medical trade and creating an ener-getic research community. The Artificial Intelligence in Medicine magazine has posted a massive amount. This paper gives an overview of the history of AI applications in brain MRI analysis to research its effect at the wider studies discipline and perceive de-manding situations for its destiny. Analysis of numerous articles to create a taxono-my of research subject matters and results was done. The article is classed which might be posted between 2000 and 2018 with this taxonomy. Analyzed articles have excessive citations. Efforts are useful in figuring out popular studies works in AI primarily based on mind MRI analysis throughout specific issues. The biomedical prognosis was ruled by way of knowledge engineering research in its first decade, whilst gadget mastering, and records mining prevailed thereafter. Together these two topics have contributed a lot to the latest medical domain

The effect of repetitive head impact exposure on white matter lesion volume

Contact and collision sports (CCS) expose athletes to countless repetitive head impacts (RHI) across a single season, potentially leading to increased risk of long-term difficulties in cognition and the development of neurodegenerative disease. There is mixed literature on whether RHI from CCS result in changes to white matter and long-term neurobehavioral outcomes, therefore this research project seeks to provide supporting evidence by comparing the total volume of fluid-attenuated inversion recovery (FLAIR) white matter lesions in individuals with a history of RHI from CCS to those without a history of RHI from the Boston University Alzheimer’s Disease Research Center (BU ADRC). The RHI participants were matched to a group of non-RHI participants based on age (+/- 5 years). Effects of RHI on white matter hyperintensities (WMHs) are evaluated, while considering hippocampal volume across RHI and non-RHI groups. When controlling for age, sex, education, and total hippocampal volume, those with a history of football were found to have a significantly greater WMH volume (p=.02) compared to those without a history of football play. Compared to the non-RHI group, the RHI group including all athletes (n=42) had a greater WMH volume, although it did not reach a level of significance (p=.91). This investigation provided preliminary evidence for a link between high RHI exposure and WMHs in football players, and a non-significant relationship between RHI and increased WMHs in those with a history of CCS compared to individuals in the non-RHI group. Future research should expand upon this investigation, by examining RHI exposure and WMH consequences in a diverse assortment of sports, follow athletes longitudinally for repeated in vivo MRIs and post-mortem neuropathological confirmation, and include more female athletes

Circle of Willis variants and cerebrovascular health: Representations, prevalences, functions and related consequences. Incomplete anatomy and changes to flow appear to induce more unfavourable health outcomes

Background: The Circle of Willis (CoW) is a circular structure of arteries in which most of the blood flowing to our brains pass through. The structure has primarily been regarded as important for its ability to redistribute blood flow in case of acute arterial occlusion, but may also have a role in dampening the pressure gradient in cerebral blood flow. The CoW anatomy also varies considerably, where its segments can be missing or thinner than normal, and therefore appears as a risk factor for cerebrovascular health. Objectives: To describe and report (I) the observed CoW variants and anatomy, and also examine the incomplete CoW variants’ associations to (II) white matter hyperintensities (WMH) and (III) saccular intracranial aneurysms (IA) compared to the complete CoW variant. Methods: Participants were invited from The Seventh Tromsø Study of which 1878 underwent magnetic resonance imaging. From the scans, CoW variants were semiautomatically classified. Likewise, WMH was automatically segmented and IAs were manually ascertained by radiologists. Results: The complete CoW is not very prevalent in participants older than 40 years old, and our findings suggest that the CoW becomes more incomplete with older age. Furthermore, incomplete CoW variants were not associated with increased WMH volume compared to the complete CoW variant. Incomplete CoW variants were associated increased odds of IA presence compared to the complete CoW variant. Conclusion: The results indicate that a complete CoW variant is not common in adults and elderly, which may have unfortunate consequences when incomplete CoW variants are associated with increased prevalence of IAs. Fortunately, not all results imply unfavourable outcomes, but further study of the CoW changes and possible effects of the variants over time are required.Bakgrunn: Willis Sirkel (CoW) er en sirkulær struktur av arterier i bunnen av hjernen som det meste av blodet går igjennom på tur til hjernen. Strukturen har vært antatt viktig for dens evner til å omdisponere blod i tilfellet arterier går tett, men i nyere tid har det også blitt foreslått at strukturen kan være viktig for å dempe pulstrykket i hjernen fra hjertet. Anatomien til CoW varierer mye, der segmenter mangler eller er tynnere enn normalt, og framstår dermed som et mulig risikomoment for hjernehelsen. Mål: Å beskrive (I) CoW varianter og anatomi. Analysere ufullstendige CoW varianters assosiasjoner til (II) vevsskader i hjernens indre som kalles hvit materie hyperintensiteter (WMH) og (III) sakkulære intrakranielle aneurismer (IA) sammenliknet med den fullstendige CoW varianten. Metoder: Deltakere ble invitert fra den Syvende Tromsøundersøkelsen hvorav 1878 ble tatt hjernebilder av med magnetresonans. Fra disse bildene ble CoW anatomi klassifisert. Likeså ble WMH automatisk segmentert og IA påvist av radiologer. Resultater: Den fullstendige CoW var ikke vanlig blant deltakerne eldre enn 40 år, og vi observerte også at CoW anatomien ble mer og mer ufullstendig hos eldre. Videre var ufullstendige CoW varianter ikke assosiert med høyere forekomst av WMH sammenliknet med den fullstendige CoW. Videre var ufullstendige CoW varianter assosiert med forhøyet odds for å ha IA sammenliknet med den fullstendige CoW. Konklusjon: Resultatene antyder at en fullstendig CoW ikke er spesielt vanlig hos voksne og eldre, noe som kan få uheldige følger når ufullstendige CoW er assosiert med økt forekomst av IA. Heldigvis antyder ikke alle resultatene negative følger, men mer forskning på CoW endringer og mulige effekter av anatomien over tid behøves for å stadfeste resultatene

Predicting the Future

Due to the increased capabilities of microprocessors and the advent of graphics processing units (GPUs) in recent decades, the use of machine learning methodologies has become popular in many fields of science and technology. This fact, together with the availability of large amounts of information, has meant that machine learning and Big Data have an important presence in the field of Energy. This Special Issue entitled “Predicting the Future—Big Data and Machine Learning” is focused on applications of machine learning methodologies in the field of energy. Topics include but are not limited to the following: big data architectures of power supply systems, energy-saving and efficiency models, environmental effects of energy consumption, prediction of occupational health and safety outcomes in the energy industry, price forecast prediction of raw materials, and energy management of smart buildings