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English [en], pdf, 42.9MB, Sanet.st_Artificial_Intelligence_in_Cancer_Diagnosis_and_Prognosis,_Volume_1.pdf
Artificial Intelligence in Cancer Diagnosis and Prognosis, Volume 1: Lung and kidney cancer
IOP Publishing, IPEM–IOP Series in Physics and Engineering in Medicine and Biology, 2022
Ayman El-Baz, Jasjit S. Suri
“Within this first volume dealing with lung and kidney cancer, the editors and authors will detail the latest research related to the application of AI to cancer diagnosis and prognosis and summarize its advantages. It's the editors and authors intention to explore how AI assists in these activities, specifically with regard to its unprecedented accuracy, which is even higher than that of general statistical applications in oncology. Ways will also be demonstrated as to how these methods in AI are advancing the field.
There have been thousands of papers written between 1995 and 2019 related to AI for cancer diagnosis and prognosis. However, to this date (and unknown to the Editors) there has not yet been published a comprehensive overview of the latest findings pertaining to these AI technologies, within a single book project(s). Therefore, the purpose of this three volume work and particularly for this first volume dealing with lung and kidney cancer, is to present a compendium of these findings related to these two pervasive cancers. Within this coverage it's our hope that scientists, researchers and clinicians can successfully incorporate these techniques into other significant cancers such as pancreatic, esophageal leukemia, melanoma, etc.
Key Features:
This work will contain a comprehensive overview of the latest techniques in Artificial Intelligence (AI) related to lung and kidney cancers. All chapter authors and contributors will be world-class researchers in various aspects of AI and appropriate subsets such as machine learning (ML), deep learning (DL) and neural networks. The fusion of 'Big Data' and 'AI' will be incorporated where appropriate. Multimodality imaging will be included within specific chapters. Extensive references will be included at the end of each chapter to enhance further study.”
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Sanet.st_Artificial_Intelligence_in_Cancer_Diagnosis_and_Prognosis,_Volume_1.pdf
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Title
Artificial Intelligence in Cancer Diagnosis and Prognosis, Volume 1: Lung and kidney cancer
Author
Ayman El-Baz, Jasjit S. Suri
Publisher
IOP Publishing
Edition/series info
IPEM–IOP Series in Physics and Engineering in Medicine and Biology, 2022
Year
2022
Description
Within this first volume dealing with lung and kidney cancer, the editors and authors will detail the latest research related to the application of AI to cancer diagnosis and prognosis and summarize its advantages. It's the editors and authors intention to explore how AI assists in these activities, specifically with regard to its unprecedented accuracy, which is even higher than that of general statistical applications in oncology. Ways will also be demonstrated as to how these methods in AI are advancing the field.
There have been thousands of papers written between 1995 and 2019 related to AI for cancer diagnosis and prognosis. However, to this date (and unknown to the Editors) there has not yet been published a comprehensive overview of the latest findings pertaining to these AI technologies, within a single book project(s). Therefore, the purpose of this three volume work and particularly for this first volume dealing with lung and kidney cancer, is to present a compendium of these findings related to these two pervasive cancers. Within this coverage it's our hope that scientists, researchers and clinicians can successfully incorporate these techniques into other significant cancers such as pancreatic, esophageal leukemia, melanoma, etc.
Key Features:
This work will contain a comprehensive overview of the latest techniques in Artificial Intelligence (AI) related to lung and kidney cancers. All chapter authors and contributors will be world-class researchers in various aspects of AI and appropriate subsets such as machine learning (ML), deep learning (DL) and neural networks. The fusion of 'Big Data' and 'AI' will be incorporated where appropriate. Multimodality imaging will be included within specific chapters. Extensive references will be included at the end of each chapter to enhance further study.
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FAQs
How is AI used in cancer diagnosis? ›
Scientists have developed AI tools to aid screening tests for several kinds of cancer, including breast cancer. AI-based computer programs have been used to help doctors interpret mammograms for more than 20 years, but research in this area is quickly evolving.
Can AI be used to cure cancer? ›In chronic disease management and prevention, especially in cancer research, AI has been critical in the diagnosis, decision-making, and treatment process. According to the National Cancer Institute, AI, machine learning, and deep learning can all be used to improve cancer care and patient outcomes.
Which AI technique can be used to predict if cancer is malignant? ›In this paper the classification algorithms are used to classify whether the tumor is benign or malignant. The supervised learning algorithms of machine learning such as logistic regression, Support vector machine and K Nearest neighbour algorithm are usually used to analyse the tumour detection.
What machine detects cancer? ›Imaging tests used in diagnosing cancer may include a computerized tomography (CT) scan, bone scan, magnetic resonance imaging (MRI), positron emission tomography (PET) scan, ultrasound and X-ray, among others.
Can AI predict cancer? ›Doctors and scientists have developed an artificial intelligence tool that can accurately predict how likely tumours are to grow back in cancer patients after they have undergone treatment.
How accurate is AI diagnosis? ›Similar to the intense practice doctors must undergo, it takes thousands of examples for an algorithm to learn how to recognize illness. In fact, with a standard accuracy of 72.52%, AI diagnoses illness even more accurately than the average doctor, who, in the same study, diagnosed with 71.4% accuracy.
What are 3 ways to cure cancer? ›- Surgery: An operation where doctors cut out tissue with cancer cells.
- Chemotherapy: Special medicines that shrink or kill cancer cells.
- Radiation therapy: Using high-energy rays (similar to X-rays) to kill cancer cells.
The most common treatments are surgery, chemotherapy, and radiation. Other options include targeted therapy, immunotherapy, laser, hormonal therapy, and others. Here is an overview of the different treatments for cancer and how they work. Surgery is a common treatment for many types of cancer.
What is the best treatment to cure cancer? ›- Surgery. The goal of surgery is to remove the cancer or as much of the cancer as possible.
- Chemotherapy. Chemotherapy uses drugs to kill cancer cells.
- Radiation therapy. ...
- Bone marrow transplant. ...
- Immunotherapy. ...
- Hormone therapy. ...
- Targeted drug therapy. ...
- Cryoablation.
Medical artificial intelligence (AI) can perform with expert-level accuracy and deliver cost-effective care at scale. IBM's Watson diagnoses heart disease better than cardiologists do.
Which of the following is the most accurate and safest technique to diagnose cancer? ›
Final answer: The safest technique for detecting cancers is Magnetic resonance imaging (MRI).
Which testing procedure is most accurate for detecting cancer? ›Biopsy. In most cases, doctors need to do a biopsy to be certain that you have cancer. A biopsy is a procedure in which the doctor removes a sample of abnormal tissue. A pathologist looks at the tissue under a microscope and runs other tests on the cells in the sample.
Can AI detect lung cancer? ›Currently, the FDA have approved several AI programs in CXR and chest CT reading, which enables AI systems to take part in lung cancer detection. Following the success of AI application in the radiology field, AI was applied to digitalized whole slide imaging (WSI) annotation.
What cancers don't show up in blood work? ›Aside from leukemia, most cancers cannot be detected in routine blood work, such as a CBC test. However, specific blood tests are designed to identify tumor markers, which are chemicals and proteins that may be found in the blood in higher quantities than normal when cancer is present.
What color is cancer on a CT scan? ›Cancer cells take up the contrast, which makes them appear white on the scan. This in turn allows your radiologist to better interpret the images, which is important when making a diagnosis. He or she will also be able to more clearly see tissues surrounding a potentially cancerous lesion, including nearby organs.
What diseases can be detected by AI? ›Researchers have used various AI-based techniques such as machine and deep learning models to detect the diseases such as skin, liver, heart, alzhemier, etc. that need to be diagnosed early.
What does AI mean in cancer? ›Terms | Definitions |
---|---|
Artificial neural network | A computional model in machine learning, which is inspired by the biological structures and functions of the human brain |
In medicine, the use of AI may help improve cancer screening and diagnosis and plan treatment. It may also be used in research and in drug discovery and development. Also called artificial intelligence.
Can you trust artificial intelligence? ›Just like humans, AI systems can make mistakes. For example, a self-driving car might mistake a white tractor-trailer truck crossing a highway for the sky. But to be trustworthy, AI needs to be able to recognize those mistakes before it is too late.
Can AI tell right from wrong? ›Artificial intelligence has made it possible for machines to do all sorts of useful new things. But they still don't know right from wrong.
What are 3 negative effects of artificial intelligence? ›
- High Costs. The ability to create a machine that can simulate human intelligence is no small feat. ...
- No creativity. A big disadvantage of AI is that it cannot learn to think outside the box. ...
- Unemployment. ...
- 4. Make Humans Lazy. ...
- No Ethics. ...
- Emotionless. ...
- No Improvement.
Curable Cancers: Prostate, Thyroid, Testicular, Melanoma, Breast.
How can I stop cancer cells from growing naturally? ›- Don't use tobacco. Smoking has been linked to many types of cancer, including cancer of the lung, mouth, throat, voice box, pancreas, bladder, cervix and kidney. ...
- Eat a healthy diet. ...
- Maintain a healthy weight and be physically active. ...
- Protect yourself from the sun.
Remission. It doesn't happen often, but some cancers can go into remission even if they are stage 4.
What is the most hard to treat cancer? ›Some of the most difficult cancers to treat are those that develop in the: liver. pancreas. ovaries.
How to survive cancer without chemo? ›- Treatment 1: Surgery. ...
- Treatment 2: Immunotherapy. ...
- Treatment 3: Targeted therapies. ...
- Treatment 4: Active surveillance. ...
- Treatment 5: Supportive care.
Oncolytic viruses kill individual cancer cells, but studies also suggest that they can boost the immune system's ability to recognize and kill a tumor. The viruses enter tumor cells specifically and replicate, eventually breaking the cells apart.
How does AI help in disease detection? ›Known as SISH (self-supervised image search for histology), the new tool acts like a search engine for pathology images and has many potential applications, including identifying rare diseases and helping clinicians determine which patients are likely to respond to similar therapies.
Why is machine learning used in cancer detection? ›Key approaches include screening patients who are at risk but have no symptoms, and rapidly and appropriately investigating those who do. Machine learning, whereby computers learn complex data patterns to make predictions, has the potential to revolutionise early cancer diagnosis.
How does AI work in medical imaging? ›Researchers have applied AI to automatically recognizing complex patterns in imaging data and providing quantitative assessments of radiographic characteristics. In radiation oncology, AI has been applied on different image modalities that are used at different stages of the treatment.