Edukasi Tentang Pengenalan Tanda Gejala, Pencegahan dan Penanganan Kanker Kulit Sebagai Dampak Paparan Sinar Matahari dan Penggunaan Kosmetik Berbahan Kimia Berbahaya di Poli Kulit Rumah Sakit Akademik Universitas Mataram

Penulis

Niti Wedayani , Novia Andansari Putri R , Dedianto Hidajat

DOI:

10.29303/jpmpi.v5i3.2133

Diterbitkan:

2022-09-15

Terbitan:

Vol 5 No 3 (2022): Juli - September

Kata Kunci:

Skin Cancer, Ultraviolet Light.

Artikel

Unduhan

Cara Mengutip

Wedayani, N., Putri R, N. A., & Hidajat, D. (2022). Edukasi Tentang Pengenalan Tanda Gejala, Pencegahan dan Penanganan Kanker Kulit Sebagai Dampak Paparan Sinar Matahari dan Penggunaan Kosmetik Berbahan Kimia Berbahaya di Poli Kulit Rumah Sakit Akademik Universitas Mataram . Jurnal Pengabdian Magister Pendidikan IPA, 5(3), 223–226. https://doi.org/10.29303/jpmpi.v5i3.2133

Metrik

Metrik sedang dimuat ...

Abstrak

Skin cancer is characterized by uncontrolled growth of skin cells, which can damage the surrounding tissue and can spread to other parts of the body. Ultraviolet radiation from the sun is the main cause of skin cancer. UV rays can damage the DNA that makes up genes. Chemicals, sunlight together with viruses are also other causative factors from outside the body. Health workers play an important role in providing education related to the health of the people of West Nusa Tenggara. Lack of public knowledge about the main causes of skin cancer, signs and symptoms, and how to prevent it, is the responsibility of health workers, to reduce the mortality rate caused by malignancy. The approach steps taken in this program are counseling or providing education to visitors to the skin and genital polyclinic at the Mataram University Hospital. Community service was carried out in the hall of UNRAM Hospital and Dermatology and Venereology Clinic of UNRAM Hospital by distributing flyers and also providing education through counseling about the importance of Skin Care. There were 12 participants and 13 patients visiting the skin and sex polyclinic at UNRAM Hospital. Before being given education, participants were asked to fill out a knowledge questionnaire about Ca Skin. Of the questionnaires given 22 people have less knowledge about the risk factors for skin cancer, signs and symptoms of skin cancer and what to do when it occurs. 3 other people know the risk factors for skin cavities and their signs and symptoms.

Referensi

Esteva A; Kuprel B; Novoa RA et al.2017.Dermatologist-level classification of skin cancer with deep neural networks.Nature. 2017; 542: 115-118.

Ferlay J, Soerjomataram I, Dikshit R, et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer 2015; 136: E359–86.

Haenssle HA, Fink C, Schneiderbauer R, et al. Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists. Ann Oncol 2018; 29: 1836–42.

Han SS, Park I, Eun Chang S, et al. Augmented intelligence dermatology: deep neural networks empower medical professionals in diagnosing skin cancer and predicting treatment options for 134 skin disorders. J Invest Dermatol 2020; 140: 1753–61.

International Skin Imaging Collaboration. ISIC Archive. http:// www.isic-archive.com/ (accessed March 11, 2021)

Tschandl P, Rosendahl C, Akay BN, et al. Expert-level diagnosis of nonpigmented skin cancer by combined convolutional neural networks. JAMA Dermatol 2019; 155: 58–65.

Biografi Penulis

Niti Wedayani, Fakultas Kedokteran, Universitas Mataram, Mataram, Indonesia

Novia Andansari Putri R, Fakultas Kedokteran, Universitas Mataram, Mataram, Indonesia

Dedianto Hidajat, Fakultas Kedokteran, Universitas Mataram, Mataram, Indonesia

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