Sophia, the smart humanoid! People around the world wish to talk to her or see her in real life. Sometimes listening to her interviews, her knowledge about various fields and her thought process as natural intelligence makes us forget that she is an Artificially Intelligent robotic machine; created by Hanson Robotics and an excellent example of AI, ML and Deep Learning.
This robot is getting ready to revolutionize health care sector and the humanoid is already being used to help research autism and other diseases.
Sophia at ITU’s AI for Good Global Summit in Geneva in May 2018
Artificial Intelligence is ready to rule the world. Machines are becoming smarter day by day to help people. These technologies are constantly interacting with human beings and started understanding human speech. Amazon echo and Google home are the best examples available in the market today for general consumers. Even consider self-driving car or Military simulations, we can find AI everywhere. It also plays a major role in Government, Gaming, e-ticket booking, Cab Service, Financial Industry and e-commerce.
Types of AI
Artificial Intelligence in Healthcare
Health and wellness, cancer treatment, dentistry, medical diagnosis, radiology tools, pathology, smart devices and surgery are the medical fields where AI is used. In the last couple of years, the usage of AI in the medical field has grown so much that most of the top companies are investing huge capital in AI development for the betterment of the Human Race.
The Benefits of Artificial Intelligence in Healthcare:
- It can be used to assist doctors to make better decisions which can improve the accuracy of medical diagnosis such as cancer detection, fracture detection and various other ailments.
- AI is being used in dentistry for smile correction and other detections.
- It will help in suggesting better treatment and reduce human errors.
- Provides online care and patient assistance using Chatbots or Voicebots which helps in reducing patient’s frequent hospital visit as well as it stores required information to the medical records and helps in cost reduction.
In most of the cases researchers uses Machine Learning technology where a model is created by feeding large amount of medical data. The algorithm is defined in such a way that the images are being used to learn the model with certain parameters which helps in certain diagnosis or predictions of disease.
Also, read the blog on CRM for Healthcare
Cancer Detection, Bone Fracture Detection, Detection of various disease from body fluid or blood, Dental detections are the few topics where AI/ML has helped doctors make better decisions.
AI diagnoses are performed using a neural network which helps in mapping patterns from data to specific outcome. Machine Learning and deep learning algorithms are being used for model creation. Large number of medical data is collected from hospitals and image pre-processing is performed for image enhancement and cleaning. After which image segmentation is performed for feature extraction and with the help of extracted feature the medical images are classified using classifiers like CNN and SVM algorithms.
Large numbers of data such as DICOM or x-rays are being used for training of a machine learning model using image classifiers. Large image samples helps in better accuracy and prediction.
The Image Data Set for ML Model Preparation Consists Of Three Phases:
- Training Phase
- Validation Phase
- Testing Phase
Once the model gets generated after training phase it will undergo validation phase where the parameters are being tuned for better prediction results. In testing phase images are tested for accuracy of disease prediction model.
AI in medical field will help in early detection of disease and suggestion of proper treatment will help save lot of lives. Doctors and various medical sectors are going to benefit from AI technologies. Not only in medical field but it can also be used in many other fields to ease human efforts in their day to day operations. Thus, the AI in future will make human life much simpler and easier.