Deep Learning for Head Pose Estimation: A Survey

Head pose estimation (HPE) is an active and popular area of research. Over the years, many approaches have constantly been developed, leading to a progressive improvement in accuracy; nevertheless, head pose estimation remains an open research topic, especially in unconstrained environments. In this paper, we will review the increasing amount of available datasets and the modern methodologies used to estimate orientation, with a special attention to deep learning techniques. We will discuss the evolution of the feld by proposing a classifcation of head pose estimation methods, explaining their advantages and disadvantages, and highlighting the diferent ways deep learning techniques have been used in the context of HPE. An in-depth performance comparison and discussion is presented at the end of the work. We also highlight the most promising research directions for future investigations on the topic

Hemostasis in uncontrolled esophageal variceal bleeding by self-expanding metal stents. A systematic review

Aim: The aim of this systematic review was to evaluate the current reported efficacy and the mortality rate of SEMS treatment in uncontrolled bleeding patients. Background: Esophageal variceal bleeding (EVB) represents a life threatening pathology. Despite the adequate pharmacologic and endoscopic treatment, continuous or recurrent bleeding, named as uncontrolled bleeding, occurs in 10-20% of cases. A new removable, covered, and self-expanding metal stent (SEMS) was proposed to control the variceal bleeding. Materials and methods: The study was conducted according to the PRISMA statement. Studies were identified by searching MEDLINE (1989-present) and SCOPUS (1989-present) databases. The last search was run on 01 July 2015. Results: Nine studies (period range=2002-2015) met the inclusion criteria and were included in quantitative analysis. High rate of SEMS efficacy in controling acute bleeding was observed, with a reported percentage ranging from 77.7 to 100%. In 10% to 20% of patients, re-bleeding occurred with SEMS in situ. Stent deployment was successful in 77.8% to 100% of patients while 11 to 36.5% of patients experienced stent migration. Conclusion: SEMS could be effective and safe in control EVB and can be proposed as a reliable option to ballon tamponed for patient stabilization and as a bridging to other therapeutic approach. Keywords: Nonselective β-blockers, TIPSS, Endoscopic band ligation, Uncontrolled bleeding, Selfexpanding metal stent

Effect of external PEEP in patients under controlled mechanical ventilation with an auto-PEEP of 5 cmH2O or higher.

In some patients with auto-positive end-expiratory pressure (auto-PEEP), application of PEEP lower than auto-PEEP maintains a constant total PEEP, therefore reducing the inspiratory threshold load without detrimental cardiovascular or respiratory effects. We refer to these patients as complete PEEP-absorbers. Conversely, adverse effects of PEEP application could occur in patients with auto-PEEP when the total PEEP rises as a consequence. From a pathophysiological perspective, all subjects with flow limitation are expected to be complete PEEP-absorbers, whereas PEEP should increase total PEEP in all other patients. This study aimed to empirically assess the extent to which flow limitation alone explains a complete PEEP-absorber behavior (i.e., absence of further hyperinflation with PEEP), and to identify other factors associated with it.One hundred patients with auto-PEEP of at least 5 cmH2O at zero end-expiratory pressure (ZEEP) during controlled mechanical ventilation were enrolled. Total PEEP (i.e., end-expiratory plateau pressure) was measured both at ZEEP and after applied PEEP equal to 80 % of auto-PEEP measured at ZEEP. All measurements were repeated three times, and the average value was used for analysis.Forty-seven percent of the patients suffered from chronic pulmonary disease and 52 % from acute pulmonary disease; 61 % showed flow limitation at ZEEP, assessed by manual compression of the abdomen. The mean total PEEP was 7 ± 2 cmH2O at ZEEP and 9 ± 2 cmH2O after the application of PEEP (p < 0.001). Thirty-three percent of the patients were complete PEEP-absorbers. Multiple logistic regression was used to predict the behavior of complete PEEP-absorber. The best model included a respiratory rate lower than 20 breaths/min and the presence of flow limitation. The predictive ability of the model was excellent, with an overoptimism-corrected area under the receiver operating characteristics curve of 0.89 (95 % CI 0.80-0.97).Expiratory flow limitation was associated with both high and complete PEEP-absorber behavior, but setting a relatively high respiratory rate on the ventilator can prevent from observing complete PEEP-absorption. Therefore, the effect of PEEP application in patients with auto-PEEP can be accurately predicted at the bedside by measuring the respiratory rate and observing the flow-volume loop during manual compression of the abdomen

L’adenocarcinoma dell’appendice ileo-ciecale: presentazione di un caso clinico e revisione della letteratura

L’adenocarcinoma dell’appendice ileo-ciecale è una neoplasia di rara osservazione rappresentando meno dello 0,5% di tutti i tumori dell’apparato gastrointestinale. Nella maggior parte dei casi viene diagnosticato all’esame istologico definitivo di un’appendice asportata per flogosi, talora invece rappresenta un reperto del tutto inatteso, documentato da biopsie estemporanee, in corso di intervento chirurgico eseguito per sospetta appendicite acuta o altra patologia non appendicolare. La storia naturale di tale neoplasia è fortemente condizionata dalle peculiari caratteristiche anatomiche del viscere che ne favoriscono la precoce diffusione e una notevole tendenza alla perforazione. Si associa frequentemente ad altre neoplasie primitive, sincrone o metacrone, a localizzazione colo-rettale o extraintestinale. Il trattamento chirurgico oncologicamente corretto è l’emicolectomia destra che può essere eseguita come prima procedura, nei casi in cui la neoplasia venga diagnosticata pre- o intraoperatoriamente, o come seconda procedura, due-tre settimane dopo l’appendicectomia, qualora soltanto l’esame istologico dell’appendice asportata riveli la presenza dell’adenocarcinoma. L’emicolectomia destra è il trattamento chirurgico più idoneo in tutti gli istotipi (colico, mucinoso, adenocarcinoide), in presenza di perforazione ed anche nelle neoplasie allo stadio A di Dukes. Durante l’atto operatorio è necessario effettuare un’accurata esplorazione della cavità addominale per la ricerca di neoplasie sincrone, mentre dopo l’intervento i pazienti dovranno essere sottoposti ad un follow-up regolare e prolungato nel tempo onde diagnosticare precocemente eventuali neoplasie metacrone. Riportiamo il caso di una donna di 78 anni con adenocarcinoma dell’appendice scoperto casualmente in corso di intervento chirurgico eseguito per un quadro di occlusione intestinale da sospetta neoplasia del cieco

A deep learning approach for Spatio-Temporal forecasting of new cases and new hospital admissions of COVID-19 spread in Reggio Emilia, Northern Italy

Since February 2020, the COVID-19 epidemic has rapidly spread throughout Italy. Some studies showed an association of environmental factors, such as PM10, PM2.5, NO2, temperature, relative humidity, wind speed, solar radiation and mobility with the spread of the epidemic. In this work, we aimed to predict via Deep Learning the real-time transmission of SARS-CoV-2 in the province of Reggio Emilia, Northern Italy, in a grid with a small resolution (12&nbsp;km&nbsp;×&nbsp;12&nbsp;km), including satellite information

Thyroid Imaging Reporting and Data System Score Combined with the New Italian Classification for Thyroid Cytology Improves the Clinical Management of Indeterminate Nodules

The new Italian cytological classification (2014) of thyroid nodules replaced the TIR3 category of the old classification (2007) with two subclasses, TIR3A and TIR3B, with the aim of reducing the rate of surgery for benign diseases. Moreover, thyroid imaging reporting and data system (TI-RADS) score appears to ameliorate the stratification of the malignancy risk. We evaluated whether the new Italian classification has improved diagnostic accuracy and whether its association with TI-RADS score could improve malignancy prediction. We retrospectively analyzed 70 nodules from 70 patients classified as TIR3 according to the old Italian classification who underwent surgery for histological diagnosis. Of these, 51 were available for cytological revision according to the new Italian cytological classification. Risk of malignancy was determined for TIR3A and TIR3B, TI-RADS score, and their combination. A different rate of malignancy (p=0.0286) between TIR3A (13.04%) and TIR3B (44.44%) was observed. Also TI-RADS score is significantly (p=0.003) associated with malignancy. By combining cytology and TI-RADS score, patients could be divided into three groups with low (8.3%), intermediate (21.4%), and high (80%) risk of malignancy. In conclusion, the new Italian cytological classification has an improved diagnostic accuracy. Interestingly, the combination of cytology and TI-RADS score offers a better stratification of the malignancy risk

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Clinical features and outcomes of elderly hospitalised patients with chronic obstructive pulmonary disease, heart failure or both

Background and objective: Chronic obstructive pulmonary disease (COPD) and heart failure (HF) mutually increase the risk of being present in the same patient, especially if older. Whether or not this coexistence may be associated with a worse prognosis is debated. Therefore, employing data derived from the REPOSI register, we evaluated the clinical features and outcomes in a population of elderly patients admitted to internal medicine wards and having COPD, HF or COPD + HF. Methods: We measured socio-demographic and anthropometric characteristics, severity and prevalence of comorbidities, clinical and laboratory features during hospitalization, mood disorders, functional independence, drug prescriptions and discharge destination. The primary study outcome was the risk of death. Results: We considered 2,343 elderly hospitalized patients (median age 81 years), of whom 1,154 (49%) had COPD, 813 (35%) HF, and 376 (16%) COPD + HF. Patients with COPD + HF had different characteristics than those with COPD or HF, such as a higher prevalence of previous hospitalizations, comorbidities (especially chronic kidney disease), higher respiratory rate at admission and number of prescribed drugs. Patients with COPD + HF (hazard ratio HR 1.74, 95% confidence intervals CI 1.16-2.61) and patients with dementia (HR 1.75, 95% CI 1.06-2.90) had a higher risk of death at one year. The Kaplan-Meier curves showed a higher mortality risk in the group of patients with COPD + HF for all causes (p = 0.010), respiratory causes (p = 0.006), cardiovascular causes (p = 0.046) and respiratory plus cardiovascular causes (p = 0.009). Conclusion: In this real-life cohort of hospitalized elderly patients, the coexistence of COPD and HF significantly worsened prognosis at one year. This finding may help to better define the care needs of this population

Antidiabetic Drug Prescription Pattern in Hospitalized Older Patients with Diabetes

Objective: To describe the prescription pattern of antidiabetic and cardiovascular drugs in a cohort of hospitalized older patients with diabetes. Methods: Patients with diabetes aged 65 years or older hospitalized in internal medicine and/or geriatric wards throughout Italy and enrolled in the REPOSI (REgistro POliterapuie SIMI—Società Italiana di Medicina Interna) registry from 2010 to 2019 and discharged alive were included. Results: Among 1703 patients with diabetes, 1433 (84.2%) were on treatment with at least one antidiabetic drug at hospital admission, mainly prescribed as monotherapy with insulin (28.3%) or metformin (19.2%). The proportion of treated patients decreased at discharge (N = 1309, 76.9%), with a significant reduction over time. Among those prescribed, the proportion of those with insulin alone increased over time (p = 0.0066), while the proportion of those prescribed sulfonylureas decreased (p &lt; 0.0001). Among patients receiving antidiabetic therapy at discharge, 1063 (81.2%) were also prescribed cardiovascular drugs, mainly with an antihypertensive drug alone or in combination (N = 777, 73.1%). Conclusion: The management of older patients with diabetes in a hospital setting is often sub-optimal, as shown by the increasing trend in insulin at discharge, even if an overall improvement has been highlighted by the prevalent decrease in sulfonylureas prescription