Efficient shallow learning as an alternative to deep learning

The realization of complex classification tasks requires training of deep learning (DL) architectures consisting of tens or even hundreds of convolutional and fully connected hidden layers, which is far from the reality of the human brain. According to the DL rationale, the first convolutional layer reveals localized patterns in the input and large-scale patterns in the following layers, until it reliably characterizes a class of inputs. Here, we demonstrate that with a fixed ratio between the depths of the first and second convolutional layers, the error rates of the generalized shallow LeNet architecture, consisting of only five layers, decay as a power law with the number of filters in the first convolutional layer. The extrapolation of this power law indicates that the generalized LeNet can achieve small error rates that were previously obtained for the CIFAR-10 database using DL architectures. A power law with a similar exponent also characterizes the generalized VGG-16 architecture. However, this results in a significantly increased number of operations required to achieve a given error rate with respect to LeNet. This power law phenomenon governs various generalized LeNet and VGG-16 architectures, hinting at its universal behavior and suggesting a quantitative hierarchical time-space complexity among machine learning architectures. Additionally, the conservation law along the convolutional layers, which is the square-root of their size times their depth, is found to asymptotically minimize error rates. The efficient shallow learning that is demonstrated in this study calls for further quantitative examination using various databases and architectures and its accelerated implementation using future dedicated hardware developments.Comment: 26 pages, 4 figures (improved figures resolution

Enhancing the success rates by performing pooling decisions adjacent to the output layer

Learning classification tasks of (2^nx2^n) inputs typically consist of \le n (2x2) max-pooling (MP) operators along the entire feedforward deep architecture. Here we show, using the CIFAR-10 database, that pooling decisions adjacent to the last convolutional layer significantly enhance accuracy success rates (SRs). In particular, average SRs of the advanced VGG with m layers (A-VGGm) architectures are 0.936, 0.940, 0.954, 0.955, and 0.955 for m=6, 8, 14, 13, and 16, respectively. The results indicate A-VGG8s' SR is superior to VGG16s', and that the SRs of A-VGG13 and A-VGG16 are equal, and comparable to that of Wide-ResNet16. In addition, replacing the three fully connected (FC) layers with one FC layer, A-VGG6 and A-VGG14, or with several linear activation FC layers, yielded similar SRs. These significantly enhanced SRs stem from training the most influential input-output routes, in comparison to the inferior routes selected following multiple MP decisions along the deep architecture. In addition, SRs are sensitive to the order of the non-commutative MP and average pooling operators adjacent to the output layer, varying the number and location of training routes. The results call for the reexamination of previously proposed deep architectures and their SRs by utilizing the proposed pooling strategy adjacent to the output layer.Comment: 27 pages, 3 figures, 1 table and Supplementary Informatio

The mechanism underlying successful deep learning

Deep architectures consist of tens or hundreds of convolutional layers (CLs) that terminate with a few fully connected (FC) layers and an output layer representing the possible labels of a complex classification task. According to the existing deep learning (DL) rationale, the first CL reveals localized features from the raw data, whereas the subsequent layers progressively extract higher-level features required for refined classification. This article presents an efficient three-phase procedure for quantifying the mechanism underlying successful DL. First, a deep architecture is trained to maximize the success rate (SR). Next, the weights of the first several CLs are fixed and only the concatenated new FC layer connected to the output is trained, resulting in SRs that progress with the layers. Finally, the trained FC weights are silenced, except for those emerging from a single filter, enabling the quantification of the functionality of this filter using a correlation matrix between input labels and averaged output fields, hence a well-defined set of quantifiable features is obtained. Each filter essentially selects a single output label independent of the input label, which seems to prevent high SRs; however, it counterintuitively identifies a small subset of possible output labels. This feature is an essential part of the underlying DL mechanism and is progressively sharpened with layers, resulting in enhanced signal-to-noise ratios and SRs. Quantitatively, this mechanism is exemplified by the VGG-16, VGG-6, and AVGG-16. The proposed mechanism underlying DL provides an accurate tool for identifying each filter's quality and is expected to direct additional procedures to improve the SR, computational complexity, and latency of DL.Comment: 33 pages, 8 figure

The association between socio-demographic characteristics and adherence to breast and colorectal cancer screening: Analysis of large sub populations

<p>Abstract</p> <p>Background</p> <p>Populations having lower socioeconomic status, as well as ethnic minorities, have demonstrated lower utilization of preventive screening, including tests for early detection of breast and colorectal cancer.</p> <p>The objective</p> <p>To explore socio-demographic disparities in adherence to screening recommendations for early detection of cancer.</p> <p>Methods</p> <p>The study was conducted by Maccabi Healthcare Services, an Israeli HMO (health plan) providing healthcare services to 1.9 million members. Utilization of breast cancer (BC) and colorectal cancer (CC) screening were analyzed by socio-economic ranks (SERs), ethnicity (Arab vs non-Arab), immigration status and ownership of voluntarily supplemental health insurance (VSHI).</p> <p>Results</p> <p>Data on 157,928 and 303,330 adults, eligible for BC and CC screening, respectively, were analyzed. Those having lower SER, Arabs, immigrants from Former Soviet Union countries and non-owners of VSHI performed fewer cancer screening examinations compared with those having higher SER, non-Arabs, veterans and owners of VSHI (p < 0.001). Logistic regression model for BC Screening revealed a positive association with age and ownership of VSHI and a negative association with being an Arab and having a lower SER. The model for CC screening revealed a positive association with age and ownership of VSHI and a negative association with being an Arab, having a lower SER and being an immigrant. The model estimated for BC and CC screening among females revealed a positive association with age and ownership of VSHI and a negative association with being an Arab, having a lower SER and being an immigrant.</p> <p>Conclusion</p> <p>Patients from low socio-economic backgrounds, Arabs, immigrants and those who do not own supplemental insurance do fewer tests for early detection of cancer. These sub-populations should be considered priority populations for targeted intervention programs and improved resource allocation.</p

The anti-vaccination movement and resistance to allergen-immunotherapy: a guide for clinical allergists

Despite over a century of clinical use and a well-documented record of efficacy and safety, a growing minority in society questions the validity of vaccination and fear that this common public health intervention is the root-cause of severe health problems. This article questions whether growing public anti-vaccine sentiments might have the potential to spill-over into other therapies distinct from vaccination, namely allergen-immunotherapy. Allergen-immunotherapy shares certain medical vernacular with vaccination (e.g., allergy shots, allergy vaccines), and thus may become "guilty by association" due to these similarities. Indeed, this article demonstrates that anti-vaccine websites have begun unduly discrediting this allergy treatment regimen. Following an explanation of the anti-vaccine movement, the article aims to provide guidance on how clinicians can respond to patient fears towards allergen-immunotherapy in the clinical setting. This guide focuses on the provision of reliable information to patients in order to dispel misconceived associations between vaccination and allergen-immunotherapy, and the discussion of the risks and benefits of both therapies in order to assist patients in making autonomous decisions about their choice of allergy treatment

Diminishing benefits of urban living for children and adolescents’ growth and development

Optimal growth and development in childhood and adolescence is crucial for lifelong health and well-being1–6. Here we used data from 2,325 population-based studies, with measurements of height and weight from 71 million participants, to report the height and body-mass index (BMI) of children and adolescents aged 5–19 years on the basis of rural and urban place of residence in 200 countries and territories from 1990 to 2020. In 1990, children and adolescents residing in cities were taller than their rural counterparts in all but a few high-income countries. By 2020, the urban height advantage became smaller in most countries, and in many high-income western countries it reversed into a small urban-based disadvantage. The exception was for boys in most countries in sub-Saharan Africa and in some countries in Oceania, south Asia and the region of central Asia, Middle East and north Africa. In these countries, successive cohorts of boys from rural places either did not gain height or possibly became shorter, and hence fell further behind their urban peers. The difference between the age-standardized mean BMI of children in urban and rural areas was <1.1 kg m–2 in the vast majority of countries. Within this small range, BMI increased slightly more in cities than in rural areas, except in south Asia, sub-Saharan Africa and some countries in central and eastern Europe. Our results show that in much of the world, the growth and developmental advantages of living in cities have diminished in the twenty-first century, whereas in much of sub-Saharan Africa they have amplified