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A study on Deep Machine Learning Algorithms for diagnosis of diseases
| Content Provider | Semantic Scholar |
|---|---|
| Author | J. Dinu A. Joseph, Felix Orlando Maria |
| Copyright Year | 2017 |
| Abstract | Consider that we are living in a place that is far away from a hospital or do not have sufficient money to cover up the hospital bill or do not have enough time to take off work. In such cases, the disease diagnosis through sophisticated machines would be lifesaving. Scientists had developed numerous artificially intelligent diagnosis algorithms for detecting various diseases like Rheumatoid Arthritis, Cancer, Lung Diseases, Heart Diseases, Diabetic Retinopathy, Hepatitis Disease, Alzheimer's disease, Liver Disease, Dengue Disease and Parkinson Disease. Deep learning uses large artificial neural networks layers having interconnected nodes which can rearrange themselves as and when new information comes in. This technique allows the computers to self-learn on their own without the need for human programming. This paper focuses on recent developments in machine learning which have made significant impacts in the detection and diagnosis of various diseases. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www.ripublication.com/ijaer17/ijaerv12n17_03.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
