USING ARTIFICIAL INTELLIGENCE (AI) TO IMPROVE SKIN CANCER SCREENING

An Academic presentation byDr. Nancy Agens, Head, Technical Operations, Pubrica Group: www.pubrica.comEmail: sales@pubrica.com

Introduction

Usage of AI Technology

Skin Imaging

AI for Screening Skin Cancer

Convolutional Neural Network (CNN)

Conclusion

Outline of Topics

Today's Discussion

Introduction

The very extreme cancer has shown its nature of the effect and has spread to almost all the body organs like bone cancer, lung cancer, breast cancer, colon cancer, skin cancer etc.

Cancer society, like the American Cancer Society, National Cancer Institute, World Health Organization has defined cancer as a spread of anomaly cells in an uncontrolled fashion in the diseased organ.

It was estimated that overall deaths have come up to 9.6 million during 2018, and in the year 2019, 1.7 million new cases of cancer were yet to be diagnosed.

Most of the cancers spread the disease internally without showing any external symptoms in the body, but skin cancer spread extra growth lump which appears externally.

AI technology can be implemented in different sectors of healthcare data, either structured or unstructured.

The most widespread AI techniques applied are machine learning methodologies to analyse structured data and for unstructured data analysis neural network and classical support vector machine, natural language processing and modern deep learning.

The most prevalent usage of AI tools in screening diseases like cardiology, cancer and neurology.

Usage of AI Technology

Skin Imaging

AI technology is apt to dermatology to recognize and capture the image for diagnosis.

Patches on the skin are screened by dermoscopy, reflectance confocal microscopy (RCM) and very high-frequency (VHF), however, each technology of skin imaging has its own advantages and disadvantages.

The skin imaging technology has gained its significance in the clinical diagnosis of skin cancer, and these techniques are widely accepted by the entire dermatologist in worldwide.

AI for Screening Skin Cancer

It has become essential to overcome various skin problems, even though doctors screen the skin cancer patients with sophisticated diagnostic tools, the post diagnosis, treatment and response to the treatment and drugs depends on the inter-individual variation.

Moreover, screening the skin cancer patient involves invasive method like a biopsy of skin tissue and examining for the cause of cancer, which is a laborious process.

To avoid incision and time consumption, doctors introduced the non-invasive application of Artificial Intelligence to screen skin cancer patients.

Although AI technology is a new tool for screening skin cancer, it is still at a very early stage.

Convolutional Neural Network (CNN)

Deep learning Convolutional Neural Network (CNN) was found to be the better diagnostic tool for screening skin cancer.

CNN diagnose by capturing images and moles on the skin through an artificial neural network and can differentiate the skin cancer between benign and malignant lesions quickly, which will help physicians to biopsy a lesion or not.

Moreover, the advancement of deep neural network installed in mobile devices can guide the doctors even when outside the clinic.

Artificial intelligence (AI) technology is helping doctors to draw a significant conclusion about patient’s reports.

Medical imaging systems after performing a scan to the human body deliver signals if it detects anomalies and can guide doctors to screen the anomaly to save the patient’s life.

In the case of patients with skin cancer, the use of Automated Total Body Mapping along with AI results in better consistency in the earliest detection of skin cancer.

AI cannot replace human intelligence and experience in the detection of skin cancer: In the end, the doctor decides what to do.”

Conclusion

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