Revolutionizing Cancer Treatment: AI Breakthroughs Slash Diagnosis Times, Saving Lives Faster

We humans have been fighting cancer for a long time. This deadly disease was first recorded in ancient Egypt around 5,000 years ago. Since then, researchers, medical professionals and patient caregivers have been giving it their all. He has helped make great strides in the understanding, diagnosis, treatment and cure of this disease.

However, cancer remains an increasingly serious threat. The disease causes approximately 10 million deaths per year worldwide. And the World Health Organization (WHO) predicts there will be more than 35 million new cancer cases in 2050, up 77% from the estimated 20 million cases in 2022.

Nowadays, cancer treatment is an issue of great importance all over the world. Modern technology has played an important role in advancing research more rapidly. and helps reduce costs significantly. As a result, the situation in the fight against this deadly disease has changed a lot.

Cloud technology has the advantage of being easily scalable. and the costs are not very high. This allows health agencies and patients to deal with the disease more effectively. From the beginning of the disease until the moment of recovery, AI (Artificial Intelligence) and ML (Machine Learning) technologies help us understand genetic information. Deeper medical information and imaging Make data analysis fast and with secure access to information on demand Researchers around the world can collaborate in real time. and quickly exchange important information. Furthermore, remote patient monitoring systems and telemedicine also help patients to be more involved in the treatment process.

However, technology is not a miracle capable of eradicating all cancers. Rather, it is a tool that helps researchers and medical staff work more efficiently. The technology enables search efficiency and better results. It makes diagnosis faster and more precise. and help accelerate the drug discovery and development process. It also increases access to services through remote treatment channels and clinical trials covering multiple patient groups.

This research uses genome sequence analysis techniques to gain a deeper understanding of cancer. Cancer is a disease caused by abnormal and uncontrolled cell division. Most are the result of some form of genetic variation. Therefore, cancer is considered a DNA disease. What makes cancer difficult to treat is When the genes are mutated Its nature will change. And as the cancer grows it continues to change, although each type of cancer has its own unique set of mutations. But in that same tumor the genetic and cellular mutations are also different.

Investigating genetic diversity requires enormous amounts of data. But data collection must be done carefully and securely to protect patient privacy. Then analyze and present the data in an easy-to-understand format so doctors can use it. Including use as a guideline for treatment and development of new drugs.

The Cancer Genome Atlas project collected data from more than 20,000 tumors and comparative normal tissue samples from 11,328 cancer patients across 33 cancer types. A graphical presentation of the data shows how each type of cancer develops and spreads. Both forms of stem cells Genetic changes caused by various viruses and communication processes within the body can be used to effectively treat diseases. This project is part of the AWS Registry of Open Data and helps researchers around the world access and expand their knowledge base.

Finding the genetic code of cancer with that information It is necessary to analyze each patient’s DNA sequence in an efficient and cost-effective way. That’s the goal of California-based Ultima Genomics. This company has invented a new generation of faster and cheaper DNA analysis tools. Use AWS cloud services for analytics. This tool can analyze the entire human genome for just $100. Just 10 years ago this analysis cost $1,000.

A new genome sequence analysis technique invented by Ultima Genomics. Helps detect cancer more quickly. Thanks to its low-cost genetic analysis methods, the Munich Leukemia Laboratory uses Amazon Elastic Compute Cloud (Amazon EC2) to process genomic data. Processing time can be reduced from 20 hours to just 3 hours. It makes diagnosis faster and more precise.

Usually, most patients are not diagnosed with cancer through extensive genetic analysis. But it is often detected by going to the doctor for an annual checkup. or because they have other abnormal symptoms that do not appear to be related to cancer. Therefore, doctors may notice small signs on images that could indicate cancer. Although at that time this was not the main purpose of the doctor’s visit. It is considered one of the most important ways in which artificial intelligence can help increase the chances of survival of cancer patients.

Michael Rivers, vice president of digital pathology at Roche Tissue Diagnostics, which has partnered with Ibex and AWS to bring AI-based diagnostic tools to pathology labs through the Navify platform, said: “Most cancer diagnosis is based still on tissue on a slide using a microscope. Digitizing those slides gives us the opportunity to apply image analysis via artificial intelligence to help diagnose and determine treatment plans for patients.”

Michael explains that one of the most interesting ways that AI can speed up the diagnosis process is by training the base model. (Fundamental Models: FM) to be able to analyze the images yourself. “Making AI easily explain its processes is critical to the solutions we are developing,” Michael said. We will have heat maps to tell medical experts how the AI ​​system is analyzing the images, but the final diagnosis will be at the expert’s discretion.”

Fighting cancer isn’t just about providing faster, more effective treatments. This is because cancer is spreading more and more. Increasing access to care for all is therefore equally important. And it is important to ensure that future treatments are developed with all cancer patients in mind.

in many remote areas of China There are ultrasound experts. It is used very little (ultrasound), making diagnosis difficult. Shangyiyun Company then created “Dr. J”, an AI assistant to help breast cancer screening. It also sends videos and ultrasound images to the cloud for medical experts to analyze further. Using Dr. J helps breast cancer screening be more thorough. and can quickly find patients who need further treatment With AWS data processing and storage, Dr. J can provide efficient, accurate and stable screening services to institutions and users. Additionally, AWS has rigorous data security standards to support the adoption of Dr. J. It can be used anywhere in the world with confidence

Hurone AI is using artificial intelligence technology to help fill gaps in cancer care in sub-Saharan Africa. The main technology used is an AI prediction engine and a large language model, or LLM, developed in the AWS cloud, which helps busy oncology specialists provide comprehensive patient monitoring and support. even in remote areas without medical facilities, Hurone AI is also studying how the same system can be used to select patients who can participate in clinical trials. This will help develop more effective cancer treatments for everyone.

Expanding cancer care services to more areas across the country is an important way to help more patients access services. Another way is to provide patient care services at home. This allows patients to receive treatment in a familiar environment. It makes you feel relaxed, encouraged and makes you feel like you have more control over your life.

What poses a challenge to the medical community in treating cancer Each person has different symptoms and physical conditions. Just like the genes of each cancerous tumor are different. Using cloud technology in patient care This helps treatment better meet and cover each person’s specific needs. Turn these challenges into healing strengths. In addition to making physical treatment more effective, this technology is also very beneficial to the mental health of patients. This is because it will help each patient feel understood and cared for closely based on their unique condition and needs. Therefore, it not only makes physical treatment more targeted. But it also has a positive impact on patient experience and treatment outcomes.