Artificial Intelligence Models in the Diagnosis of Adult-Onset Dementia Disorders: A Review

Background: The progressive aging of populations, primarily in the industrialized western world, is accompanied by the increased incidence of several non-transmittable diseases, including neurodegenerative diseases and adult-onset dementia disorders. To stimulate adequate interventions, including treatment and preventive measures, an early, accurate diagnosis is necessary. Conventional magnetic resonance imaging (MRI) represents a technique quite common for the diagnosis of neurological disorders. Increasing evidence indicates that the association of artificial intelligence (AI) approaches with MRI is particularly useful for improving the diagnostic accuracy of different dementia types. Objectives: In this work, we have systematically reviewed the characteristics of AI algorithms in the early detection of adult-onset dementia disorders, and also discussed its performance metrics. Methods: A document search was conducted with three databases, namely PubMed (Medline), Web of Science, and Scopus. The search was limited to the articles published after 2006 and in English only. The screening of the articles was performed using quality criteria based on the Newcastle-Ottawa Scale (NOS) rating. Only papers with an NOS score ≥ 7 were considered for further review. Results: The document search produced a count of 1876 articles and, because of duplication, 1195 papers were not considered. Multiple screenings were performed to assess quality criteria, which yielded 29 studies. All the selected articles were further grouped based on different attributes, including study type, type of AI model used in the identification of dementia, performance metrics, and data type. Conclusions: The most common adult-onset dementia disorders occurring were Alzheimer's disease and vascular dementia. AI techniques associated with MRI resulted in increased diagnostic accuracy ranging from 73.3% to 99%. These findings suggest that AI should be associated with conventional MRI techniques to obtain a precise and early diagnosis of dementia disorders occurring in old age

Prevention and Management of Bleeding During Endoscopic Approaches to Skull Base Pathologies

The rate of serious permanent morbidity and mortality with endonasal approaches has declined secondary to increased knowledge of the pertinent anatomy, advanced neuroimaging and navigation techniques, better surgical instruments, and improved exposure and reconstruction strategies.1-3 Although rare, vascular injury remains a potentially serious complication. However, with limited systematically-collected and reported data, the exact incidence rate of vascular injuries is difficult to determine. In terms of arterial injuries, the incidence based on reported series likely ranges from 0.3%-9% (Table 1),4-11 with higher rates most commonly associated with chordomas and chondrosarcomas involving the clivus. Venous injury is comparatively less severe and easier to manage. As a result, there is a comparatively lower impetus to publish epidemiological data and management strategies for these injuries. The consequences of arterial injury include fatal hemorrhage, vessel occlusion or thromboembolism causing infarction, development of a pseudoaneurysm (PA), carotid-cavernous fistula (CCF), subarachnoid hemorrhage (SAH), and vasospasm.6,7,9 Surgical expertise and detailed knowledge of the neurovascular anatomy is critical to the avoidance and management of vascular injuries. Pages: 20-2

Minimally invasive simple prostatectomy: Robotic-assisted versus laparoscopy. A comparative study

Purpose: Robotic-assisted simple prostatectomy (RASP) is a novel surgical procedure for the management of obstructive symptoms caused by enlarged prostate glands. Before the introduction of minimally invasive techniques, the standard approach was the open simple prostatectomy (OSP). The aim of our study was to compare intraoperative and perioperative outcomes of robotic (RASP) and laparoscopic (LSP) simple prostatectomy. Methods: We retrospectively analyzed data from patients who underwent minimally invasive simple prostatectomy at the Urological Department of Portogruaro Hospital, Portogruaro, and at the Urological Department of "San Bassiano" Hospital, in Bassano del Grappa, from March 2015 to December 2020. Data collected from medical records included age, body mass index, prostate volume, operative time, preoperative International Prostatic Symptoms Score (IPSS), postoperative IPSS, time with drainage, blood transfusion, intraoperative complications, perioperative complications and length of hospital stay. Results: Robotic-assisted (n = 25) and laparoscopic simple prostatectomy (n = 25) were performed with a transvesical approach. No significant differences were observed regarding baseline characteristics, body mass index, prostate volume and IPSS. Operative time was lower in the laparoscopic group (122 min vs 139 min) (p = 0.024), while hospital stay was lower in the robotic group (4 days vs 6 days) (p = 0.047). Conclusions: Robotic-assisted simple prostatectomy is a safe technique with results comparable to laparoscopic simple prostatectomy, encompassing the advantage of a shorter hospitalization. Considering the costs and the limited availability of robotic-assisted simple prostatectomy, laparoscopic simple prostatectomy is a valid and safe alternative for experienced surgeons

Bounding Helly numbers via Betti numbers

We show that very weak topological assumptions are enough to ensure the existence of a Helly-type theorem. More precisely, we show that for any non-negative integers $b$ and $d$ there exists an integer $h(b,d)$ such that the following holds. If $\mathcal F$ is a finite family of subsets of $\mathbb R^d$ such that $\tilde\beta_i\left(\bigcap\mathcal G\right) \le b$ for any $\mathcal G \subsetneq \mathcal F$ and every $0 \le i \le \lceil d/2 \rceil-1$ then $\mathcal F$ has Helly number at most $h(b,d)$. Here $\tilde\beta_i$ denotes the reduced $\mathbb Z_2$-Betti numbers (with singular homology). These topological conditions are sharp: not controlling any of these $\lceil d/2 \rceil$ first Betti numbers allow for families with unbounded Helly number. Our proofs combine homological non-embeddability results with a Ramsey-based approach to build, given an arbitrary simplicial complex $K$, some well-behaved chain map $C_*(K) \to C_*(\mathbb R^d)$.Comment: 29 pages, 8 figure

Managing the Socially Marginalized: Attitudes Towards Welfare, Punishment and Race

Welfare and incarceration policies have converged to form a system of governance over socially marginalized groups, particularly racial minorities. In both of these policy areas, rehabilitative and social support objectives have been replaced with a more punitive and restrictive system. The authors examine the convergence in individual-level attitudes concerning welfare and criminal punishment, using national survey data. The authors\u27 analysis indicates a statistically significant relationship between punitive attitudes toward welfare and punishment. Furthermore, accounting for the respondents\u27 racial attitudes explains the bivariate relationship between welfare and punishment. Thus, racial attitudes seemingly link support for punitive approaches to opposition to welfare expenditures. The authors discuss the implications of this study for welfare and crime control policies by way of the conclusion

On the use of cartographic projections in visualizing phylo-genetic tree space

Phylogenetic analysis is becoming an increasingly important tool for biological research. Applications include epidemiological studies, drug development, and evolutionary analysis. Phylogenetic search is a known NP-Hard problem. The size of the data sets which can be analyzed is limited by the exponential growth in the number of trees that must be considered as the problem size increases. A better understanding of the problem space could lead to better methods, which in turn could lead to the feasible analysis of more data sets. We present a definition of phylogenetic tree space and a visualization of this space that shows significant exploitable structure. This structure can be used to develop search methods capable of handling much larger data sets