14 research outputs found
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
Worldwide trends in underweight and obesity from 1990 to 2022: a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults
Background Underweight and obesity are associated with adverse health outcomes throughout the life course. We
estimated the individual and combined prevalence of underweight or thinness and obesity, and their changes, from
1990 to 2022 for adults and school-aged children and adolescents in 200 countries and territories.
Methods We used data from 3663 population-based studies with 222 million participants that measured height and
weight in representative samples of the general population. We used a Bayesian hierarchical model to estimate
trends in the prevalence of different BMI categories, separately for adults (age ≥20 years) and school-aged children
and adolescents (age 5–19 years), from 1990 to 2022 for 200 countries and territories. For adults, we report the
individual and combined prevalence of underweight (BMI <18·5 kg/m2) and obesity (BMI ≥30 kg/m2). For schoolaged children and adolescents, we report thinness (BMI <2 SD below the median of the WHO growth reference)
and obesity (BMI >2 SD above the median).
Findings From 1990 to 2022, the combined prevalence of underweight and obesity in adults decreased in
11 countries (6%) for women and 17 (9%) for men with a posterior probability of at least 0·80 that the observed
changes were true decreases. The combined prevalence increased in 162 countries (81%) for women and
140 countries (70%) for men with a posterior probability of at least 0·80. In 2022, the combined prevalence of
underweight and obesity was highest in island nations in the Caribbean and Polynesia and Micronesia, and
countries in the Middle East and north Africa. Obesity prevalence was higher than underweight with posterior
probability of at least 0·80 in 177 countries (89%) for women and 145 (73%) for men in 2022, whereas the converse
was true in 16 countries (8%) for women, and 39 (20%) for men. From 1990 to 2022, the combined prevalence of
thinness and obesity decreased among girls in five countries (3%) and among boys in 15 countries (8%) with a
posterior probability of at least 0·80, and increased among girls in 140 countries (70%) and boys in 137 countries (69%)
with a posterior probability of at least 0·80. The countries with highest combined prevalence of thinness and
obesity in school-aged children and adolescents in 2022 were in Polynesia and Micronesia and the Caribbean for
both sexes, and Chile and Qatar for boys. Combined prevalence was also high in some countries in south Asia, such
as India and Pakistan, where thinness remained prevalent despite having declined. In 2022, obesity in school-aged
children and adolescents was more prevalent than thinness with a posterior probability of at least 0·80 among girls
in 133 countries (67%) and boys in 125 countries (63%), whereas the converse was true in 35 countries (18%) and
42 countries (21%), respectively. In almost all countries for both adults and school-aged children and adolescents,
the increases in double burden were driven by increases in obesity, and decreases in double burden by declining
underweight or thinness.
Interpretation The combined burden of underweight and obesity has increased in most countries, driven by an
increase in obesity, while underweight and thinness remain prevalent in south Asia and parts of Africa. A healthy
nutrition transition that enhances access to nutritious foods is needed to address the remaining burden of
underweight while curbing and reversing the increase in obesit