Improving the Characterization of Radiologically Isolated Syndrome Suggestive of Multiple Sclerosis

OBJECTIVE: To improve the characterization of asymptomatic subjects with brain magnetic resonance imaging (MRI) abnormalities highly suggestive of multiple sclerosis (MS), a condition named as "radiologically isolated syndrome" (RIS). METHODS: Quantitative MRI metrics such as brain volumes and magnetization transfer (MT) were assessed in 19 subjects previously classified as RIS, 20 demographically-matched relapsing-remitting MS (RRMS) patients and 20 healthy controls (HC). Specific measures were: white matter (WM) lesion volumes (LV), total and regional brain volumes, and MT ratio (MTr) in lesions, normal-appearing WM (NAWM) and cortex. RESULTS: LV was similar in RIS and RRMS, without differences in distribution and frequency at lesion mapping. Brain volumes were similarly lower in RRMS and RIS than in HC (p<0.001). Lesional-MTr was lower in RRMS than in RIS (p = 0.048); NAWM-MTr and cortical-MTr were similar in RIS and HC and lower (p<0.01) in RRMS. These values were particularly lower in RRMS than in RIS in the sensorimotor and memory networks. A multivariate logistic regression analysis showed that 13/19 RIS had ≥70% probability of being classified as RRMS on the basis of their brain volume and lesional-MTr values. CONCLUSIONS: Macroscopic brain damage was similar in RIS and RRMS. However, the subtle tissue damage detected by MTr was milder in RIS than in RRMS in clinically relevant brain regions, suggesting an explanation for the lack of clinical manifestations of subjects with RIS. This new approach could be useful for narrowing down the RIS individuals with a high risk of progression to MS

NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking

The field of neuromorphic computing holds great promise in terms of advancing computing efficiency and capabilities by following brain-inspired principles. However, the rich diversity of techniques employed in neuromorphic research has resulted in a lack of clear standards for benchmarking, hindering effective evaluation of the advantages and strengths of neuromorphic methods compared to traditional deep-learning-based methods. This paper presents a collaborative effort, bringing together members from academia and the industry, to define benchmarks for neuromorphic computing: NeuroBench. The goals of NeuroBench are to be a collaborative, fair, and representative benchmark suite developed by the community, for the community. In this paper, we discuss the challenges associated with benchmarking neuromorphic solutions, and outline the key features of NeuroBench. We believe that NeuroBench will be a significant step towards defining standards that can unify the goals of neuromorphic computing and drive its technological progress. Please visit neurobench.ai for the latest updates on the benchmark tasks and metrics

NeuroBench:Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking

The field of neuromorphic computing holds great promise in terms of advancing computing efficiency and capabilities by following brain-inspired principles. However, the rich diversity of techniques employed in neuromorphic research has resulted in a lack of clear standards for benchmarking, hindering effective evaluation of the advantages and strengths of neuromorphic methods compared to traditional deep-learning-based methods. This paper presents a collaborative effort, bringing together members from academia and the industry, to define benchmarks for neuromorphic computing: NeuroBench. The goals of NeuroBench are to be a collaborative, fair, and representative benchmark suite developed by the community, for the community. In this paper, we discuss the challenges associated with benchmarking neuromorphic solutions, and outline the key features of NeuroBench. We believe that NeuroBench will be a significant step towards defining standards that can unify the goals of neuromorphic computing and drive its technological progress. Please visit neurobench.ai for the latest updates on the benchmark tasks and metrics

NeuroBench:A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems

Neuromorphic computing shows promise for advancing computing efficiency and capabilities of AI applications using brain-inspired principles. However, the neuromorphic research field currently lacks standardized benchmarks, making it difficult to accurately measure technological advancements, compare performance with conventional methods, and identify promising future research directions. Prior neuromorphic computing benchmark efforts have not seen widespread adoption due to a lack of inclusive, actionable, and iterative benchmark design and guidelines. To address these shortcomings, we present NeuroBench: a benchmark framework for neuromorphic computing algorithms and systems. NeuroBench is a collaboratively-designed effort from an open community of nearly 100 co-authors across over 50 institutions in industry and academia, aiming to provide a representative structure for standardizing the evaluation of neuromorphic approaches. The NeuroBench framework introduces a common set of tools and systematic methodology for inclusive benchmark measurement, delivering an objective reference framework for quantifying neuromorphic approaches in both hardware-independent (algorithm track) and hardware-dependent (system track) settings. In this article, we present initial performance baselines across various model architectures on the algorithm track and outline the system track benchmark tasks and guidelines. NeuroBench is intended to continually expand its benchmarks and features to foster and track the progress made by the research community

Economic consequences of investing in anti-HCV antiviral treatment from the Italian NHS perspective : a real-world-based analysis of PITER data

OBJECTIVE: We estimated the cost consequence of Italian National Health System (NHS) investment in direct-acting antiviral (DAA) therapy according to hepatitis C virus (HCV) treatment access policies in Italy. METHODS: A multistate, 20-year time horizon Markov model of HCV liver disease progression was developed. Fibrosis stage, age and genotype distributions were derived from the Italian Platform for the Study of Viral Hepatitis Therapies (PITER) cohort. The treatment efficacy, disease progression probabilities and direct costs in each health state were obtained from the literature. The break-even point in time (BPT) was defined as the period of time required for the cumulative costs saved to recover the Italian NHS investment in DAA treatment. Three different PITER enrolment periods, which covered the full DAA access evolution in Italy, were considered. RESULTS: The disease stages of 2657 patients who consecutively underwent DAA therapy from January 2015 to December 2017 at 30 PITER clinical centres were standardized for 1000 patients. The investment in DAAs was considered to equal €25 million, €15 million, and €9 million in 2015, 2016, and 2017, respectively. For patients treated in 2015, the BPT was not achieved, because of the disease severity of the treated patients and high DAA prices. For 2016 and 2017, the estimated BPTs were 6.6 and 6.2 years, respectively. The total cost savings after 20 years were €50.13 and €55.50 million for 1000 patients treated in 2016 and 2017, respectively. CONCLUSIONS: This study may be a useful tool for public decision makers to understand how HCV clinical and epidemiological profiles influence the economic burden of HCV

L'Italia come modello per l'Europa e per il mondo nelle politiche sanitarie per il trattamento dell'epatite cronica da HCV

The World Health Organization foresees the elimination of HCV infection by 2030. In light of this and the curre nt, nearly worldwide, restriction in direct-acting agents (DAA) accessibility due to their high price, we aimed to evaluate the cost-effectiveness of two alternative DAA treatment policies: Policy 1 (universal): treat all patients, regardless of the fibrosis stage; Policy 2 (prioritized): treat only priori tized patients and delay treatment of the remaining patients until reaching stage F3. T he model was based on patient’s data from the PITER cohort. We demonstrated that extending HC V treatment of patients in any fibrosis stage improves health outcomes and is cost-effective

I piani di Pierce

Si introduce la nozione di M-P-piano e si caratterizzano gli M-P-piani in quanto piani ottenibili da piani affini ordinati desarguesiani mediante una costruzione di “tipo Moulton”.The notion of M-P-planes is investigated. The main result: they are charcterized by the fact that they can be obtained from ordered affine desarguesian planes by means of a suitable construction of “Moulton type”