Early Prevention and Detection of Skin Cancer Risk using Data Mining

Ahmed, Kawsar; Jesmin, Tasnuba; Rahman, Md. Zamilur

doi:10.5120/10065-4662

Cited by 37 publications

(12 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Data is inconsistent, noisy and incomplete in the existed world. 28 29 Raw data is highly susceptible to missing values or inconsistency and affected the result analysis process. So, data cleaning is a mandatory step for mining or statistical analysis.…”

Section: Methodsmentioning

confidence: 99%

Depression and Quality of Life among Postmenopausal Women in Bangladesh: A Cross-sectional Study

et al. 2017

Self Cite

View full text Add to dashboard Cite

ObjectivesThe aims of the research are to examine the problems of abnormal menopausal women: the relationship between depression and menopausal-specific quality of life (MENQOL)-symptoms among postmenopausal women; the association of MENQOL-symptoms between pre- and postmenopausal female society in Bangladeshi real community.MethodsThis cross sectional study was conducted on 435 women of Tangail, aged (≥ 17) years, using a structured questionnaire where is inaacluded the information of MENQOL and one of the main outcomes “depression” is measured by beck depression inventory.ResultsMenopausal status and MENQOL symptoms (except pain) are significantly (P < 0.05) associated. By using post-hoc analysis, the proportion of menopausal women, classified as having a depressive mood of early menopause is significantly higher than natural-menopause. Among postmenopausal women, there is a significant correlation between “concentration problem” and “depression”. Here mean depression score (29.40 ± 6.42) of menopausal women who have any difficulty in concentrating is higher than mean depression score (20.89 ± 6.64) of menopausal women who have no difficulty in concentrating. Another six factors (osteoporosis, heart-beating, fatigue, pressure, tingling, headaches) of MENQOL-symptoms were significantly correlated with depression and P-values are 0.000, 0.000, 0.000, 0.033, 0.006, and 0.002, respectively. Finally the presence of “difficulty in concentrating” and “fatigue” are strongly associated factors with depression score (P < 0.001).ConclusionsThe early postmenopausal women have to face more psychological problems (e.g., depression) compare to others. Among postmenopausal women, there is no significant relation between depression and vasomotor symptom (e.g., hot-flashes) perspective to menopausal female society of Bangladesh.

show abstract

Section: Methodsmentioning

confidence: 99%

Depression and Quality of Life among Postmenopausal Women in Bangladesh: A Cross-sectional Study

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…The classification process of data into diverse classes according to derived constrains comparatively an individual classifier [4]- [7]. Diabetes prediction system has the main objective of prediction of diabetes among particular or certain age of people suffered by type-I [8]. Machine learning system is applied to design the diabetes system.…”

Section: Related Workmentioning

confidence: 99%

Prediction of Type 1 Diabetes Mellitus using Datamining Techniques

Saminathan*

2019

IJEAT

View full text Add to dashboard Cite

Type1 diabetes is a sickness occurs when your immune system fighting against infection, affects and erode the insulin generating beta cells of the pancreas. In general, when the blood sugar stage increases, the pancreas makes more insulin. Insulin helps to go sugar out of the blood so it can be used for liveliness. Type 1 diabetes occurs due to the immune system which affects cells in the pancreas that make insulin. The pancreas cannot make adequate insulin, so the blood sugar level continues to increase. According to the children history of type 1 diabetes may enhance risk of their life. Type 1 diabetes cannot be cured, but it can be controlled and managed. In this study we use Naive Bayes, linear regression and k-means algorithm for data analysis and prediction. It predicts the diabetes affected children with maximum level of accuracy 96% by using of data mining algorithms.

show abstract

“…Each pixel in that region is having similar attributes. Otsu's thresholding algorithms used in segmentation [5]. To segment (separate ) the region of interest the foreground and the background of the gray scaled image has to be differentiated the histogram of the original image is calculated and used to do this as its in terms of binary transformation to calculate the histogram maximum entropy method is applied Fig 8 shows the segmented image.…”

Section: Noise Removal and Binarizationmentioning

confidence: 99%

Implementation of Support Vector Machine for Identification of Skin Cancer

Neela¹

2019

IJEM

View full text Add to dashboard Cite

Skin cancer is one of the most death causing cancer with the increase of infections on skin due to various parameters of the nature, atmosphere and geographical area .The abnormal growth of skin cells has become common in today's world this abnormal growth is termed as skin cancer. Skin cancer mostly develops on the part of the skin which is exposed to sun light continuously or for long duration develops on body exposed to sun light, but it can occur anywhere on the body. Skin cancer in beginning stage is curable. Patient's life can be saving from skin cancer by early & fast detection. Early detection of skin cancer in achievable at beginning stage with the new technology. Biopsy method was used to detect the cancer in the earlier days. During biopsy, a small part of the skin tissue is extracted from the carcinoma patient; this part of the tissue will be processed in various laboratories for the identification of the presence of infected cells and the stage at which the cancer is in. Biopsy was a very time consuming and painful for the patients, and the result of biopsy process was not accurate and correct. To overcome the loner procedure and to increase the accuracy Support Vector Machine Algorithm was used in identifying the infection/ Carcinoma at the early stage and cure the infection before it leads to death.

show abstract

Early Prevention and Detection of Skin Cancer Risk using Data Mining

Cited by 37 publications

References 6 publications

Depression and Quality of Life among Postmenopausal Women in Bangladesh: A Cross-sectional Study

Depression and Quality of Life among Postmenopausal Women in Bangladesh: A Cross-sectional Study

Prediction of Type 1 Diabetes Mellitus using Datamining Techniques

Implementation of Support Vector Machine for Identification of Skin Cancer

Contact Info

Product

Resources

About