scholarly journals Intelligent Dermatologist Tool for Classifying Multiple Skin Cancer Subtypes by Incorporating Manifold Radiomics Features Categories

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Omneya Attallah ◽  
Maha Sharkas
Keyword(s):  
Skin Cancer ◽  
Binary Classification ◽  
Survival Rates ◽  
Skin Lesions ◽  
Accurate Diagnosis ◽  
Computer Assisted ◽  
Discrete Wavelet ◽  
Cancer Subtypes ◽  
Low Level ◽  
High Level

The rates of skin cancer (SC) are rising every year and becoming a critical health issue worldwide. SC’s early and accurate diagnosis is the key procedure to reduce these rates and improve survivability. However, the manual diagnosis is exhausting, complicated, expensive, prone to diagnostic error, and highly dependent on the dermatologist’s experience and abilities. Thus, there is a vital need to create automated dermatologist tools that are capable of accurately classifying SC subclasses. Recently, artificial intelligence (AI) techniques including machine learning (ML) and deep learning (DL) have verified the success of computer-assisted dermatologist tools in the automatic diagnosis and detection of SC diseases. Previous AI-based dermatologist tools are based on features which are either high-level features based on DL methods or low-level features based on handcrafted operations. Most of them were constructed for binary classification of SC. This study proposes an intelligent dermatologist tool to accurately diagnose multiple skin lesions automatically. This tool incorporates manifold radiomics features categories involving high-level features such as ResNet-50, DenseNet-201, and DarkNet-53 and low-level features including discrete wavelet transform (DWT) and local binary pattern (LBP). The results of the proposed intelligent tool prove that merging manifold features of different categories has a high influence on the classification accuracy. Moreover, these results are superior to those obtained by other related AI-based dermatologist tools. Therefore, the proposed intelligent tool can be used by dermatologists to help them in the accurate diagnosis of the SC subcategory. It can also overcome manual diagnosis limitations, reduce the rates of infection, and enhance survival rates.

scholarly journals Teaching Skin Cancer Detection to Medical Students Using a Dermoscopic Algorithm

PRiMER ◽  
2021 ◽  
Vol 5 ◽  
Author(s):  
Peggy R. Cyr ◽  
Wendy Craig ◽  
Hadjh Ahrns ◽  
Kathryn Stevens ◽  
Caroline Wight ◽  
...  
Keyword(s):  
Primary Care ◽  
Medical Students ◽  
Skin Cancer ◽  
Primary Care Physicians ◽  
Survival Rates ◽  
Family Physicians ◽  
Skin Lesions ◽  
Posttest Score ◽  
Malignant Skin ◽  
Attending Physicians

Introduction: Early detection of melanoma skin cancer improves survival rates. Training family physicians in dermoscopy with the triage amalgamated dermoscopic algorithm (TADA) has high sensitivity and specificity for identifying malignant skin neoplasms. In this study we evaluated the effectiveness of TADA training among medical students, compared with practicing clinicians. Methods: We incorporated the TADA framework into 90-minute workshops that taught dermoscopy to family physicians, primary care residents, and first- and second-year medical students. The workshop reviewed the clinical and dermoscopic features of benign and malignant skin lesions and included a hands-on interactive session using a dermatoscope. All participants took a 30-image pretest and a different 30-image posttest. Results: Forty-six attending physicians, 25 residents, and 48 medical students participated in the workshop. Mean pretest scores were 20.1, 20.3, and 15.8 for attending physicians, resident physicians and students, respectively (P<.001); mean posttest scores were 24.5, 25.9, and 24.1, respectively (P=.11). Pre/posttest score differences were significant (P<.001) for all groups. The medical students showed the most gain in their pretest and posttest scores. Conclusion: After short dermoscopy workshop, medical students perform as well as trained physicians in identifying images of malignant skin lesions. Dermoscopy training may be a valuable addition to the medical school curriculum as this skill can be used by primary care physicians as well as multiple specialists including dermatologists, gynecologists, otolaryngologists, plastic surgeons, and ophthalmologists, who often encounter patients with concerning skin lesions.

A Study on Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images

2015 ◽  
Vol 6 (4) ◽  
pp. 51-61
Author(s):  
Ebtihal Abdullah Al-Mansour ◽  
Arfan Jaffar
Keyword(s):  
Skin Cancer ◽  
Imaging Techniques ◽  
Automatic Segmentation ◽  
Survival Rates ◽  
Skin Lesions ◽  
Incidence Rates ◽  
Automated System ◽  
Final State ◽  
Survey Paper ◽  
Real Scenario

Malignant Melanoma is one of the rare and the deadliest form of skin cancer if left untreated. Death rate due to this cancer is three times more than all other skin-related malignancies combined. Incidence rates of melanoma have been increasing, especially among young adults, but survival rates are high if detected early. There is a need for an automated system to assess a patient's risk of melanoma using digital dermoscopy, that is, a skin imaging technique widely used for pigmented skin lesion inspection. Although many automated and semi-automated methods are available to diagnose skin cancer but each has its own limitations and there is no final, state-of-the art technique to date which is able to be implemented in real scenario. This survey paper is based on techniques used to segment the skin cancer, analysis of their merits and demerits and their applications on advanced imaging techniques.

scholarly journals Deep Hybrid Convolutional Neural Network for Segmentation of Melanoma Skin Lesion

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Cheng-Hong Yang ◽  
Jai-Hong Ren ◽  
Hsiu-Chen Huang ◽  
Li-Yeh Chuang ◽  
Po-Yin Chang
Keyword(s):  
Image Segmentation ◽  
Skin Cancer ◽  
Skin Lesion ◽  
Survival Rates ◽  
Skin Lesions ◽  
Manual Segmentation ◽  
Cure Rate ◽  
Dice Coefficient ◽  
Skin Imaging ◽  
Low Efficiency

Melanoma is a type of skin cancer that often leads to poor prognostic responses and survival rates. Melanoma usually develops in the limbs, including in fingers, palms, and the margins of the nails. When melanoma is detected early, surgical treatment may achieve a higher cure rate. The early diagnosis of melanoma depends on the manual segmentation of suspected lesions. However, manual segmentation can lead to problems, including misclassification and low efficiency. Therefore, it is essential to devise a method for automatic image segmentation that overcomes the aforementioned issues. In this study, an improved algorithm is proposed, termed EfficientUNet++, which is developed from the U-Net model. In EfficientUNet++, the pretrained EfficientNet model is added to the UNet++ model to accelerate segmentation process, leading to more reliable and precise results in skin cancer image segmentation. Two skin lesion datasets were used to compare the performance of the proposed EfficientUNet++ algorithm with other common models. In the PH2 dataset, EfficientUNet++ achieved a better Dice coefficient (93% vs. 76%–91%), Intersection over Union (IoU, 96% vs. 74%–95%), and loss value (30% vs. 44%–32%) compared with other models. In the International Skin Imaging Collaboration dataset, EfficientUNet++ obtained a similar Dice coefficient (96% vs. 94%–96%) but a better IoU (94% vs. 89%–93%) and loss value (11% vs. 13%–11%) than other models. In conclusion, the EfficientUNet++ model efficiently detects skin lesions by improving composite coefficients and structurally expanding the size of the convolution network. Moreover, the use of residual units deepens the network to further improve performance.

A Study on Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images

2017 ◽  
pp. 1357-1367
Author(s):  
Ebtihal Abdullah Al-Mansour ◽  
M. Arfan Jaffar
Keyword(s):  
Skin Cancer ◽  
Imaging Techniques ◽  
Automatic Segmentation ◽  
Survival Rates ◽  
Skin Lesions ◽  
Incidence Rates ◽  
Automated System ◽  
Final State ◽  
Survey Paper ◽  
Real Scenario

Malignant Melanoma is one of the rare and the deadliest form of skin cancer if left untreated. Death rate due to this cancer is three times more than all other skin-related malignancies combined. Incidence rates of melanoma have been increasing, especially among young adults, but survival rates are high if detected early. There is a need for an automated system to assess a patient's risk of melanoma using digital dermoscopy, that is, a skin imaging technique widely used for pigmented skin lesion inspection. Although many automated and semi-automated methods are available to diagnose skin cancer but each has its own limitations and there is no final, state-of-the art technique to date which is able to be implemented in real scenario. This survey paper is based on techniques used to segment the skin cancer, analysis of their merits and demerits and their applications on advanced imaging techniques.

A Study on Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images

Oncology ◽  
2017 ◽  
pp. 559-569
Author(s):  
Ebtihal Abdullah Al-Mansour ◽  
Arfan Jaffar
Keyword(s):  
Skin Cancer ◽  
Imaging Techniques ◽  
Automatic Segmentation ◽  
Survival Rates ◽  
Skin Lesions ◽  
Incidence Rates ◽  
Automated System ◽  
Final State ◽  
Survey Paper ◽  
Real Scenario

Malignant Melanoma is one of the rare and the deadliest form of skin cancer if left untreated. Death rate due to this cancer is three times more than all other skin-related malignancies combined. Incidence rates of melanoma have been increasing, especially among young adults, but survival rates are high if detected early. There is a need for an automated system to assess a patient's risk of melanoma using digital dermoscopy, that is, a skin imaging technique widely used for pigmented skin lesion inspection. Although many automated and semi-automated methods are available to diagnose skin cancer but each has its own limitations and there is no final, state-of-the art technique to date which is able to be implemented in real scenario. This survey paper is based on techniques used to segment the skin cancer, analysis of their merits and demerits and their applications on advanced imaging techniques.

Influence of low-frequency variability on high and low groundwater levels: example of aquifers in northern France

2021 ◽  
Author(s):  
Lisa Baulon ◽  
Nicolas Massei ◽  
Delphine Allier ◽  
Matthieu Fournier ◽  
Hélène Bessiere
Keyword(s):  
Groundwater Level ◽  
Low Frequency ◽  
Discrete Wavelet ◽  
Groundwater Levels ◽  
Low Level ◽  
Northern France ◽  
Low Frequency Variability ◽  
Low Levels ◽  
High Level ◽  
Very High

<p>Groundwater fluctuations exhibit very often well-pronounced low-frequency variability (multi-annual to decadal timescales), linked to catchment and aquifer ability to smooth out rapid fluctuations from precipitation (low-pass filtering), especially when their characteristic time is long. This low-frequency variability, generated by large-scale climate variability and modulated by the physical properties of hydrosystems, is clearly imprinted in aquifers of northern France. Many recent researches addressed the issue of the capability of global climate models to reproduce low-frequency variability (most of the time multidecadal). For hydrological processes such as groundwater levels, which variance can be dominated by such low-frequency ranges, it may then appear crucial to provide assessment on how very high or very low levels are sensitive to such low-frequency variability. In this study, we investigate how low-frequency variability (from multi-annual to interdecadal timescales) may generate very high or very low groundwater levels (higher or lower than percentiles 80% and 20%, respectively). To test such hypotheses, our approach consists of breaking down groundwater level signals into timescale components using maximum overlap discrete wavelet transform in order to get wavelet details at different timescales. Multi-annual ~7 yr and interdecadal ~17 yr components appeared to be the dominant components of low-frequency variability of the signals. We then substracted these components (either one or both) and simply examined how many values remained over or below the selected threshold.</p><p>Results highlight that the number of events generated by low-frequency components is consistently closely linked to their contribution to groundwater level variability. Nearly 100% of high and low groundwater levels in inertial aquifers, that exhibit a large predominance of interdecadal variability, are generated by this timescale. At least 50% of high and low groundwater levels in inertial aquifers displaying a combination of interdecadal and multi-annual variabilities are generated by the combination of these two timescales. Finally, less than 50% of high and low groundwater levels in mixed aquifers (i.e. with a well pronounced low-frequency variability superimposed to annual variability) are generated by the multi-annual and interdecadal variabilities. In all studied aquifers with various dynamics, we notice a higher sensitivity of low groundwater levels to low-frequency variability than high groundwater levels.</p><p>Across aquifers of northern metropolitan France, particularly in the chalk of the Paris Basin, we observe quite a clear dependence of well-known historical high and low groundwater levels to low-frequency variability. In particular, the 2001 high levels and the 1992 low levels are seemingly generated by concomitant multi-annual and interdecadal high levels, and concomitant multi-annual and interdecadal low levels, respectively. On the other hand, the 1995 high levels and 1998 low levels are produced by a multi-annual high level attenuated by an interdecadal low level, and a multi-annual low level attenuated by an interdecadal high level, respectively. These phasings are also observed in precipitation and effective precipitation a few time in advance (ranging from 2 months to 1.5 years). Finally, the contribution of multi-annual and interdecadal variabilities to make the groundwater levels reach or exceed one selected threshold is directly influenced by their prominence in groundwater levels variability.</p>

Teknik Data Mining Dalam Clustering Produksi Susu Segar Di Indonesia Dengan Algoritma K-Means

2019 ◽  
Vol 1 (1) ◽  
pp. 31-39
Author(s):  
Ilham Safitra Damanik ◽  
Sundari Retno Andani ◽  
Dedi Sehendro
Keyword(s):  
Data Mining ◽  
Milk Production ◽  
Clustering Algorithm ◽  
Clustering Method ◽  
Data Mining Techniques ◽  
Low Level ◽  
Fresh Milk ◽  
Nutritional Needs ◽  
High Level ◽  
Level Cluster

Milk is an important intake to meet nutritional needs. Both consumed by children, and adults. Indonesia has many producers of fresh milk, but it is not sufficient for national milk needs. Data mining is a science in the field of computers that is widely used in research. one of the data mining techniques is Clustering. Clustering is a method by grouping data. The Clustering method will be more optimal if you use a lot of data. Data to be used are provincial data in Indonesia from 2000 to 2017 obtained from the Central Statistics Agency. The results of this study are in Clusters based on 2 milk-producing groups, namely high-dairy producers and low-milk producing regions. From 27 data on fresh milk production in Indonesia, two high-level provinces can be obtained, namely: West Java and East Java. And 25 others were added in 7 provinces which did not follow the calculation of the K-Means Clustering Algorithm, including in the low level cluster.

Determinants of Abuse of the Bodies of the Dead

2019 ◽  
pp. 71-77
Author(s):  
Margarita Khomyakova
Keyword(s):  
Low Income ◽  
Criminal Code ◽  
Value Judgments ◽  
Legal Norms ◽  
Low Level ◽  
Medical Institutions ◽  
Specific Object ◽  
The Subject ◽  
The Dead ◽  
High Level

The author analyzes definitions of the concepts of determinants of crime given by various scientists and offers her definition. In this study, determinants of crime are understood as a set of its causes, the circumstances that contribute committing them, as well as the dynamics of crime. It is noted that the Russian legislator in Article 244 of the Criminal Code defines the object of this criminal assault as public morality. Despite the use of evaluative concepts both in the disposition of this norm and in determining the specific object of a given crime, the position of criminologists is unequivocal: crimes of this kind are immoral and are in irreconcilable conflict with generally accepted moral and legal norms. In the paper, some views are considered with regard to making value judgments which could hardly apply to legal norms. According to the author, the reasons for abuse of the bodies of the dead include economic problems of the subject of a crime, a low level of culture and legal awareness; this list is not exhaustive. The main circumstances that contribute committing abuse of the bodies of the dead and their burial places are the following: low income and unemployment, low level of criminological prevention, poor maintenance and protection of medical institutions and cemeteries due to underperformance of state and municipal bodies. The list of circumstances is also open-ended. Due to some factors, including a high level of latency, it is not possible to reflect the dynamics of such crimes objectively. At the same time, identification of the determinants of abuse of the bodies of the dead will reduce the number of such crimes.

Novel Nanolipoidal Systems for the Management of Skin Cancer

2020 ◽  
Vol 14 (2) ◽  
pp. 108-125
Author(s):  
Apoorva Singh ◽  
Nimisha
Keyword(s):  
Skin Cancer ◽  
Survival Rates ◽  
Cancer Therapeutics ◽  
The Body ◽  
Surgical Removal ◽  
The Novel ◽  
Skin Cancers ◽  
Recent Developments ◽  
Abnormal Cells ◽  
The Stability

: Skin cancer, among the various kinds of cancers, is a type that emerges from skin due to the growth of abnormal cells. These cells are capable of spreading and invading the other parts of the body. The occurrence of non-melanoma and melanoma, which are the major types of skin cancers, has increased over the past decades. Exposure to ultraviolet radiations (UV) is the main associative cause of skin cancer. UV exposure can inactivate tumor suppressor genes while activating various oncogenes. The conventional techniques like surgical removal, chemotherapy and radiation therapy lack the potential for targeting cancer cells and harm the normal cells. However, the novel therapeutics show promising improvements in the effectiveness of treatment, survival rates and better quality of life for patients. Different methodologies are involved in the skin cancer therapeutics for delivering the active ingredients to the target sites. Nano carriers are very efficient as they have the ability to improve the stability of drugs and further enhance their penetration into the tumor cells. The recent developments and research in nanotechnology have entitled several targeting and therapeutic agents to be incorporated into nanoparticles for an enhancive treatment of skin cancer. To protect the research works in the field of nanolipoidal systems various patents have been introduced. Some of the patents acknowledge responsive liposomes for specific targeting, nanocarriers for the delivery or co-delivery of chemotherapeutics, nucleic acids as well as photosensitizers. Further recent patents on the novel delivery systems have also been included here.

scholarly journals EXPRESS: Marketers Project Their Personal Preferences onto Consumers: Overcoming the Threat of Egocentric Decision Making

2021 ◽  
pp. 002224372199837
Author(s):  
Walter Herzog ◽  
Johannes D. Hattula ◽  
Darren W. Dahl
Keyword(s):  
Decision Making ◽  
Consumer Preferences ◽  
Research Question ◽  
Pilot Studies ◽  
Low Level ◽  
Marketing Managers ◽  
False Consensus Effect ◽  
False Consensus ◽  
High Level

This research explores how marketing managers can avoid the so-called false consensus effect—the egocentric tendency to project personal preferences onto consumers. Two pilot studies were conducted to provide evidence for the managerial importance of this research question and to explore how marketing managers attempt to avoid false consensus effects in practice. The results suggest that the debiasing tactic most frequently used by marketers is to suppress their personal preferences when predicting consumer preferences. Four subsequent studies show that, ironically, this debiasing tactic can backfire and increase managers’ susceptibility to the false consensus effect. Specifically, the results suggest that these backfire effects are most likely to occur for managers with a low level of preference certainty. In contrast, the results imply that preference suppression does not backfire but instead decreases false consensus effects for managers with a high level of preference certainty. Finally, the studies explore the mechanism behind these results and show how managers can ultimately avoid false consensus effects—regardless of their level of preference certainty and without risking backfire effects.

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