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Di postingan ini gw akan nge-share artikel yang dibuat oleh salah seorang mahasiswa/i gw mengenai Artificial Intelligence. Postingan ini salah satu bentuk apresiasi gw atas pemikiran mereka. Nama pembuat ada di judul postingan.
The use of artificial intelligence (AI) is dynamically growing nowadays. What is artificial intelligence? It is a field of study in computer science that focuses on the development of computer systems to perform tasks that require human intelligence. Examples of artificial intelligence in use are search engines, chat bots, machine translations, face recognition for phone lock, recommendations system, and games.
Artificial intelligence is used in almost all sectors, such as law, marketing and advertising, finance, retail and customer service, and healthcare. In this article, we are going to discuss more about how artificial intelligence is used in healthcare industry. The picture below tells us about several applications built using the help of artificial intelligence for helping the healthcare industry.
Fig1. Applications using AI for healthcare industry
There are several examples of artificial intelligence used in healthcare industry. First, the IBM Watson Care Manager matches individuals to a care provider that meets their needs and budget. Moreover, several hospitals are working with IBM Watson to create cognitive hospital where the app is used for identifying patient discomforts before visiting hospital and prepare the clinicians with information for helping them in delivering the appropriate treatments. In addition, the Institute of Cancer Research uses AI for making predictions about new targets for cancer drugs.
Artificial intelligence is being used in clinical care for medical imaging, echocardiography, screening for neurological conditions, surgery (robotic tools for stitching wounds), and disease detection and diagnosis.
Vast number of medical scans are collected and stored for training the AI system so that the AI could reduce the cost and time for analyzing scans, thus more scans can be taken at a time and useful for detecting conditions such as pneumonia, breast and skin cancers, and eye diseases.
Ultromics has developed echocardiography analysis technology called Topological Analysis. It is used for analyzing echocardiography scans for detecting patterns of heartbeats and diagnosing coronary heart disease, eliminating diagnostic errors by 75%.
Screening for neurological conditions
AI tools are used for analyzing speech patterns to identify and monitor symptoms of neurological disease.
Disease detection and diagnosis
- Breast cancer
AI systems can interpret mammogram data and translate patient’s charts into information that predicts the risk of breast cancer with high accuracy. Several techniques for breast cancer detection and diagnosis are neural networks, computer aided design (CAD) algorithm, fuzzy logic, linear programming, decision trees, and nearest neighbor methods. Breast cancer detection can be done by using Curemetrix algorithm, iTBra, NLP (Natural language processing) software, Genes to systems breast cancer database (G2SBC).
CAD systems are used to detect irregular mammary tissue based on mammograms which is useful for diagnosis.
iTBra, developed by Cyrcadia Health, is a smart wearable device useful for monthly breast scanning. Also, the Cyrcadia predictive algorithm will display irregular pattern when the tissue is healthy. If in the case of cancer, it will display a flat line profile.
Curemetrix algorithm creates unique breast health score for each image that can lead to improved medical image analysis.
Artificial neural network (ANN) is used for classifying cancerous and non-cancerous image. ANN technique can make a good analytical tool because ANN can learn from past examples, analyzing non-linear data, and handle imprecise information. Fuzzy logic is also used to predict the survival of patients suffering from breast cancer.
- Cardiovascular disease
Artificial neural network (ANN) is a mathematical or computational model that can be useful for the diagnosis of cardiovascular diseases by predicting heart disease based on various related factors, such as family history, alcohol intake, smoking, and age.
Baxt et al. used ANN for myocardial infarction diagnosis and the accuracy of the system is about 64%. It is also used in classification of heart sound signals measured by stethoscope in the diagnosis of heart valve conditions.
Fig2. ANN in cardiovascular disease diagnosis
- Alzheimer’s disease
Application of AI is useful for the early detection of Alzheimer’s disease. Several automated systems and tools such as Brain-computer interfaces (BCIs), Arterial spin labeling-magnetic resonance imaging (ASL-MRI), Electroencephalogram (EEG), Positron emission tomography (PET) and other algorithms are used for early detection and control the progression of the disease.
PET scan is a functional neuroimaging technique that can measure the cerebral metabolic rate for glucose, which is progressive and related to Alzheimer’s disease.
Early detection of Alzheimer’s disease by AI is useful for early treatment, which can slow down the disease progression and improving the quality of patient’s life.
Even though AI is very useful in healthcare industry, it raises some social and ethical issues. As an example, AI could make errors, such as misdiagnosis in which can cause serious implications. Second, AI systems can be hacked for gaining sensitive and private data. Last, healthcare professionals feel challenged and they are afraid that the development of AI system in healthcare industry could replace their position in the future.
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Mishra, S.G., Takke, A.K., Auti, S.T., Suryavanshi, S.V., Oza, M.J. 2017. Role of Artificial Intelligence in Health Care. BioChemistry.
2018. Artificial intelligence (AI) in healthcare and research. Nuffield Council on Bioethics.
2018. Ultromics Secures £10 Million Investment To Bring AI Heart Diagnostics To Hospitals. Finance Digest.
Kuo, E. 2017. AI in Healthcare: Industry Landscape. Techburst.
Nice article Pawitra. Keep the good work!
See you di postingan selanjutnya.