Development and validation of a machine learning-based predictive model to improve the prediction of inguinal status of anal cancer patients: A preliminary report

Introduction: The role of prophylactic inguinal irradiation (PII) in the treatment of anal cancer patients is controversial. We developped an innovative algorithm based on the Machine Learning (ML) allowing the tailoring of the prescription of PII. Results: Once verified on the independent testing set, J48 showed the better performances, with specificity, sensitivity, and accuracy rates in predicting relapsing patients of 86.4%, 50.0% and 83.1% respectively (vs 36.5%, 90.4% and 80.25%, respectively, for LR). Methods: We classified 194 anal cancer patients with Logistic Regression (LR) and other 3 ML techniques based on decision trees (J48, Random Tree and Random Forest), using a large set of clinical and therapeutic variables. We tested obtained ML algorithms on an independent testing set of 65 anal cancer patients. TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis) methodology was used for the development, the Quality Assurance and the description of the experimental procedures. Conclusion: In an internationally approved quality assurance framework, ML seems promising in predicting the outcome of patients that would benefit or not of the PII. Once confirmed in larger and/or multi-centric databases, ML could support the physician in tailoring the treatment and in deciding if deliver or not the PII

Fat Tissue’s Graft in Osteoarthritis Treatment: Indications, Preparations, and Results

Osteoarthritis (OA) represents one of the most common causes of joint pain and disability with related changes in bone morphology. In last years, this pathology is steadily increasing due to the continuous increase in the average life expectancy and the rate of active population. In recent years, there have been many conservative treatments for symptomatic gonarthrosis in order to reduce pain and delay or avoid the implantation of a knee prosthesis. The most studied and used was infiltrating treatment. Our group has been paying attention to regenerative medicine for many years, focusing on the characteristics of adipose tissue and the presence of multipotent mesenchymal cells, particularly in the vascular stromal area. Mesenchymal stem cells (MSCs) of adipose tissue can commit toward the chondrogenic, osteogenic, adipogenic, myogenic, and neurogenic lineages. Our group has continued the studies in this field by submitting this to treatment patients with grade II–III arthrosis according to the scale of Kellgren-Lawrence or patients with IV degree of such scale inoperable for internal reasons. To date, with a 4-year follow-up, our results are satisfactory in terms of pain reduction, improvement in joint function, and recovery of daily and sports activities

Case report: A multiple sclerosis patient with imaging features of glymphatic failure benefitted from CSF flow shunting

The derangement of CSF circulation impacts the functions of the glymphatic-lymphatic system (G-Ls), which regulates solute trafficking and immune surveillance in the CNS. The G-Ls failure leads to the dysregulation of clearance of waste molecules in the brain and to an altered CNS immune response. The imaging features of dilated perivascular spaces imply the impairment of the G-Ls. We report on the case of a patient with primary progressive multiple sclerosis and dilatation of perivascular spaces, who transiently improved after CSF shunt diversions. The underlying mechanisms remain to be determined and at this stage, it is not possible to link CSF diversion to an effect on MS pathology. However, this observation provides the rationale to incentivize research in the largely unknown area of CSF dynamic disturbances on G-Ls failure and ultimately in neurodegeneration

Recurrence of non-hydropic sudden sensorineural hearing loss (SSNHL): a literature review

Sudden Sensorineural Hearing Loss (SSNHL) is typically defined as the acute onset (less than 3 days) of a perceptive hearing loss of more than 30dB over at least three contiguous frequencies on pure tone audiometry. The exact incidence of SSNHL is uncertain, since many patients have a rapid and spontaneous resolution of symptoms and therefore don’t reach medical attention. Estimate of incidence ranges from 5 to 20 per 100.000 individuals, and bilateral involvement is very rare; it increases in the older patients (>65 yo)(77 per 100.000) the in younger population (<18 yo)(11 per 100.000) [3]. The true incidence of paediatric SSNHL is not established in literature; 40% of examined child with SSNHL, showed anatomic abnormaliti

Improving Educational Outcomes of English Language Learners in Schools and Programs in Boston Public Schools

Using 4 years of student-level demographic, enrollment and testing and school-level characteristics, this study analyzes the enrollment and outcomes of English Language Learners (ELLs) in Boston Public School between SY2006 and SY2009 and assess the relative impact of individual and school level factors in testing outcomes of ELLs. The study reports on the improvement in ELL dropout rates and testing outcomes during the period of observation. It reports also on the outcomes of ELLs at different levels of English proficiency and finds (1) higher dropout rates and lower testing performance among low English proficiency students; (2) a minimal proportion of students reaching academic language proficiency within the period of observation; and (3) particularly deep vulnerability among ELLs of low English proficiency entering district school in middle school and high school. In the assessment of individual and school-level factors in the testing outcomes of ELL students, the study finds English proficiency and designation as a student with disabilities are the strongest predictors of testing outcomes. Finally, the report focuses on the policy implications of these findings in view of the state’s language restrictive policies affecting the education of ELLs in Massachusetts. District level administrative and programmatic recommendations as well a state policy recommendations are provided

pMineR: An Innovative R Library for Performing Process Mining in Medicine

Process Mining is an emerging discipline investigating tasks related with the automated identification of process models, given realworld data (Process Discovery). The analysis of such models can provide useful insights to domain experts. In addition, models of processes can be used to test if a given process complies (Conformance Checking) with specifications. For these capabilities, Process Mining is gaining importance and attention in healthcare. In this paper we introduce pMineR, an R library specifically designed for performing Process Mining in the medical domain, and supporting human experts by presenting processes in a human-readable way

Identifying Success in Schools and Programs for English Language Learners in Boston Public Schools

The Gastón Institute collaborates with government agencies, community organizations and foundations in applied research aimed at evaluating the impact of policies, programs and practices. This poster describes a three-way collaboration among researchers and practitioners from Boston Public Schools (BPS), the Gastón Institute and the Center for Collaborative Education (CCE) which yielded two comprehensive studies: 1. The enrollment and outcomes of English language learners in BPS; 2. Best ELL practices in four schools that were consistently high performing or steadily improving with respect to ELL student outcomes