Rethinking the Inception Architecture for Computer Vision

Convolutional networks are at the core of most stateof-the-art computer vision solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to become mainstream, yielding substantial gains in various benchmarks. Although increased model size and computational cost tend to translate to immediate quality gains for most tasks (as long as enough labeled data is provided for training), computational efficiency and low parameter count are still enabling factors for various use cases such as mobile vision and big-data scenarios. Here we are exploring ways to scale up networks in ways that aim at utilizing the added computation as efficiently as possible by suitably factorized convolutions and aggressive regularization. We benchmark our methods on the ILSVRC 2012 classification challenge validation set demonstrate substantial gains over the state of the art: 21.2% top-1 and 5.6% top-5 error for single frame evaluation using a network with a computational cost of 5 billion multiply-adds per inference and with using less than 25 million parameters. With an ensemble of 4 models and multi-crop evaluation, we report 3.5% top-5 error and 17.3% top-1 error

The devil is in the decoder

Many machine vision applications require predictions for every pixel of the input image (for example semantic segmentation, boundary detection). Models for such problems usually consist of encoders which decreases spatial resolution while learning a high-dimensional representation, followed by decoders who recover the original input resolution and result in low-dimensional predictions. While encoders have been studied rigorously, relatively few studies address the decoder side. Therefore this paper presents an extensive comparison of a variety of decoders for a variety of pixel-wise prediction tasks. Our contributions are: (1) Decoders matter: we observe significant variance in results between different types of decoders on various problems. (2) We introduce a novel decoder: bilinear additive upsampling. (3) We introduce new residual-like connections for decoders. (4) We identify two decoder types which give a consistently high performance

Soluble and Cell-Associated Insulin Receptor Dysfunction Correlates with Severity of HAND in HIV-Infected Women

Blood sugar metabolism abnormalities have been identified in HIV-infected individuals and associated with HIV-associated neurocognitive disorders (HAND). These abnormalities may occur as a result of chronic HIV infection, long-term use of combined antiretroviral treatment (CART), aging, genetic predisposition, or a combination of these factors, and may increase morbidity and mortality in this population.To determine if changes in soluble and cell-associated insulin receptor (IR) levels, IR substrate-1 (IRS-1) levels, and IRS-1 tyrosine phosphorylation are associated with the presence and severity of HAND in a cohort of HIV-seropositive women.This is a retrospective cross-sectional study using patient database information and stored samples from 34 HIV-seropositive women and 10 controls without history of diabetes from the Hispanic-Latino Longitudinal Cohort of Women. Soluble IR subunits [sIR, ectodomain (α) and full-length or intact (αβ)] were assayed in plasma and CSF samples by ELISA. Membrane IR levels, IRS-1 levels, and IRS-1 tyrosine phosphorylation were analyzed in CSF white cell pellets (WCP) using flow cytometry. HIV-seropositive women had significantly increased levels of intact or full-length sIR in plasma (p<0.001) and CSF (p<0.005) relative to controls. Stratified by HAND, increased levels of full-length sIR in plasma were associated with the presence (p<0.001) and severity (p<0.005) of HAND. A significant decrease in IRS-1 tyrosine-phosphorylation in the WCP was also associated with the presence (p<0.02) and severity (p<0.02) of HAND.This study provides evidence that IR secretion is increased in HIV-seropositive women, and increased IR secretion is associated with cognitive impairment in these women. Thus, IR dysfunction may have a role in the progression of HAND and could represent a biomarker for the presence and severity of HAND

Long‐term efficacy and safety of once‐monthly pasireotide in Cushing's disease: A Phase III extension study

Objectives Many patients with Cushing's disease (CD) require chronic pharmacotherapy to control their hypercortisolism. We evaluated the efficacy and safety of long‐acting pasireotide during a long‐term extension study in patients with CD. Design Open‐label extension to a 12‐month Phase III study of long‐acting pasireotide in CD (N = 150; NCT01374906). Patients Patients with mean urinary free cortisol (mUFC) ≤ upper limit of normal (ULN) or receiving clinical benefit at core study end could continue long‐acting pasireotide during the extension. Results Eighty‐one of 150 (54.0%) enrolled patients entered the extension. Median overall exposure to pasireotide at study end was 23.9 months; 39/81 (48.1%) patients completed the extension (received ≥ 12 months’ treatment during the extension and could transit to a separate pasireotide safety study). mUFC was ≤ULN in 42/81 (51.9%), 13/81 (16.0%) and 43/81 (53.1%) patients at extension baseline, month (M) 36 and last assessment. Median mUFC remained within normal limits. Median late‐night salivary cortisol was 2.6 × ULN at core baseline and 1.3 × ULN at M36. Clinical improvements were sustained over time. Forty‐two (51.9%) patients discontinued during the extension: 25 (30.9%) before M24 and 17 (21.0%) after M24. Hyperglycaemia‐related AEs occurred in 39.5% of patients. Mean fasting glucose (FPG) and glycated haemoglobin (HbA1c) were stable during the extension, with antidiabetic medication initiated/escalated in some patients. Sixty‐six (81.5%) and 71 (88.9%) patients were classified as having diabetes (HbA1c ≥ 6.5%, FPG ≥ 7.0 mmol/L, antidiabetic medication use, or history of diabetes) at extension baseline and last assessment. Conclusions Long‐acting pasireotide provided sustained biochemical and clinical improvements, with no new safety signals emerging, supporting its use as an effective long‐term therapy for CD

The impact of maternal HIV infection on cord blood lymphocyte subsets and cytokine profile in exposed non-infected newborns

<p>Abstract</p> <p>Background</p> <p>Children born to HIV+ mothers are exposed intra-utero to several drugs and cytokines that can modify the developing immune system, and influence the newborn's immune response to infections and vaccines. We analyzed the relation between the distribution of cord blood lymphocyte subsets and cytokine profile in term newborns of HIV+ mothers using HAART during pregnancy and compared them to normal newborns.</p> <p>Methods</p> <p>In a prospective, controlled study, 36 mother-child pairs from HIV+ mothers and 15 HIV-uninfected mothers were studied. Hematological features and cytokine profiles of mothers at 35 weeks of pregnancy were examined. Maternal and cord lymphocyte subsets as well as B-cell maturation in cord blood were analyzed by flow cytometry. The non-stimulated, as well as BCG- and PHA-stimulated production of IL2, IL4, IL7, IL10, IL12, IFN-γ and TNF-alpha in mononuclear cell cultures from mothers and infants were quantified using ELISA.</p> <p>Results</p> <p>After one year follow-up none of the exposed infants became seropositive for HIV. An increase in B lymphocytes, especially the CD19/CD5+ ones, was observed in cord blood of HIV-exposed newborns. Children of HIV+ hard drug using mothers had also an increase of immature B-cells. Cord blood mononuclear cells of HIV-exposed newborns produced less IL-4 and IL-7 and more IL-10 and IFN-γ in culture than those of uninfected mothers. Cytokine values in supernatants were similar in infants and their mothers except for IFN-γ and TNF-alpha that were higher in HIV+ mothers, especially in drug abusing ones. Cord blood CD19/CD5+ lymphocytes showed a positive correlation with cord IL-7 and IL-10. A higher maternal age and smoking was associated with a decrease of cord blood CD4+ cells.</p> <p>Conclusions</p> <p>in uninfected infants born to HIV+ women, several immunological abnormalities were found, related to the residual maternal immune changes induced by the HIV infection and those associated with antiretroviral treatment. Maternal smoking was associated to changes in cord CD3/CD4 lymphocytes and maternal hard drug abuse was associated with more pronounced changes in the cord B cell line.</p

Updated research nosology for HIV-associated neurocognitive disorders

In 1991, the AIDS Task Force of the American Academy of Neurology published nomenclature and research case definitions to guide the diagnosis of neurologic manifestations of HIV-1 infection. Now, 16 years later, the National Institute of Mental Health and the National Institute of Neurological Diseases and Stroke have charged a working group to critically review the adequacy and utility of these definitional criteria and to identify aspects that require updating. This report represents a majority view, and unanimity was not reached on all points. It reviews our collective experience with HIV-associated neurocognitive disorders (HAND), particularly since the advent of highly active antiretroviral treatment, and their definitional criteria; discusses the impact of comorbidities; and suggests inclusion of the term asymptomatic neurocognitive impairment to categorize individuals with subclinical impairment. An algorithm is proposed to assist in standardized diagnostic classification of HAND

Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms

Importance: Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives. Objective: To evaluate whether AI can overcome human mammography interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms. Design, Setting, and Participants: In this diagnostic accuracy study conducted between September 2016 and November 2017, an international, crowdsourced challenge was hosted to foster AI algorithm development focused on interpreting screening mammography. More than 1100 participants comprising 126 teams from 44 countries participated. Analysis began November 18, 2016. Main Outcomes and Measurements: Algorithms used images alone (challenge 1) or combined images, previous examinations (if available), and clinical and demographic risk factor data (challenge 2) and output a score that translated to cancer yes/no within 12 months. Algorithm accuracy for breast cancer detection was evaluated using area under the curve and algorithm specificity compared with radiologists' specificity with radiologists' sensitivity set at 85.9% (United States) and 83.9% (Sweden). An ensemble method aggregating top-performing AI algorithms and radiologists' recall assessment was developed and evaluated. Results: Overall, 144 231 screening mammograms from 85 580 US women (952 cancer positive ≤12 months from screening) were used for algorithm training and validation. A second independent validation cohort included 166 578 examinations from 68 008 Swedish women (780 cancer positive). The top-performing algorithm achieved an area under the curve of 0.858 (United States) and 0.903 (Sweden) and 66.2% (United States) and 81.2% (Sweden) specificity at the radiologists' sensitivity, lower than community-practice radiologists' specificity of 90.5% (United States) and 98.5% (Sweden). Combining top-performing algorithms and US radiologist assessments resulted in a higher area under the curve of 0.942 and achieved a significantly improved specificity (92.0%) at the same sensitivity. Conclusions and Relevance: While no single AI algorithm outperformed radiologists, an ensemble of AI algorithms combined with radiologist assessment in a single-reader screening environment improved overall accuracy. This study underscores the potential of using machine learning methods for enhancing mammography screening interpretation

Photogrammetric method in evaluation of constitution and the body posture in pre-school children

Jednym z ważniejszych okresów posturogenezy jest koniec okresu przedszkolnego. Charakteryzuje się on intensywnym wzrostem kośćca, który zmienia proporcje ciała, nie-zakończonym procesem stabilizacji krzywizn przedniotyl-nych kręgosłupa oraz zmianą trybu życia w związku z rozpoczęciem edukacji szkolnej. Jednym z czynników warunkujących postawę ciała w tym okresie jest budowa ciała. Celem pracy była ocena postawy ciała w płaszczyźnie strzałkowej oraz ocena typu budowy ciała dzieci w wieku 6 lat. Badaniami objęto 105 dzieci z wrocławskich przedszkoli. Oceny postawy ciała w płaszczyźnie strzałkowej dokonano metodą fotogrametryczną według kryteriów Wo-lańskiego w modyfikacji Zeyland-Malawki. Typ budowy ciała określono wskaźnikiem Rohrera. Stwierdzono u wielu dzieci wady postawy ciała w płaszczyźnie strzałkowej. Osoby z postawą nieprawidłową stanowiły 38% badanych dzieci, wady występowały częściej wśród dziewcząt niż w grupie chłopców. Badane dzieci charakteryzowały się zróżnicowaniem pod względem typów budowy ciała. Dominowali osobnicy o budowie masywnej (50%), natomiast dzieci o smukłych sylwetkach było najmniej (21%). Dziewczęta o postawie prawidłowej charakteryzowała średnia budowa ciała, natomiast o postawie nieprawidłowej budowa smukła i masywna. W grupie chłopców, zarówno u osób z postawą prawidłową, jak i nieprawidłową, dominowała masywna budowa ciała.One of the most significant periods for posturogenesis is the end of the kindergarten period. It is characterized by the intensive growth of bones, which changes proportions of the body, unfinished process of stabilization of anterioposterior curvatures of spine, as well as the changes of child's lifestyle. One of determinants of the body posture within this period, is the body constitution. The aim of the study was the evaluation of the body type and the posture within the sagittal position in pre-school children. The examination was carried out in a group of 105 children, aged 6 years, from Wroclaw kindergartens. The postural evaluation was performed by means of photogrammetric method based on projection of moire pattern. The body posture of the examined children was determined by means of Wolanski's method modified by Zeyland--Malawka. The somatic type was determined for each child by means of defining the Rohrer's index. A significant number of postural defects in the sagittal plane was found. Incorrect body postures were observed in 38% of the examined children, more in girls than in boys group. The examined children were characterized by diverisification of the body build types. Stout silhouette type was dominant (50%) and the slender type was the least common (21%). The girls with incorrect body posture had the stout and slender type ot the body silhouette. In both boys groups, with correct and incorrect body posture, the stout type was dominant