How AI is Revolutionizing Healthcare
Artificial Intelligence (AI) is a broad word, and it carries a lot of weight because it covers sophisticated AI algorithms and machine learning techniques. Robots and computers can function more effectively and intelligently than regular people, thanks to these algorithms and technology. AI is the capacity for machines and robots to mimic human behavior.
How is AI Revolutionizing Medical Imaging?
Medical imaging is the process of creating images of various organs, tissues, and body parts. For example, if a person is detected with lung problems, X-rays monitor the lungs and determine which part of the lungs is affected. If the image is too blurry to make any inferences, a CT scan is utilized to acquire a better look at the lung area.
Medical imaging houses all diagnostic and therapeutic investigations and interventions carried out in a typical radiology department. The human body can be imaged using a variety of imaging modalities and procedures for diagnostic, therapeutic, and follow-up uses. It is crucial to efforts to improve the health of all population groups.
It includes the following:
- X-Rays
- Magnetic Resonance Imaging (MRI)
- Ultrasound
- Computed Tomography (CT)
At all levels of healthcare, medical imaging, especially X-rays and ultra-sonography, is essential in various clinical contexts. Accurate diagnoses are crucial for making informed choices in curative, palliative, and public health care in addition to preventative medicine.
Despite the fact that medical/clinical judgment may be sufficient for many ailments before treatment, the use of diagnostic imaging services is essential for verifying, accurately diagnosing, and recording the progression of many diseases and evaluating treatment outcomes.
Overall, the use of medical imaging has enhanced diagnosis and treatments by dramatically lowering the amount of guesswork conducted by physicians, enabling them to treat patients' wounds and illnesses more skillfully.
Medical imaging has proven essential in hospitals for detecting and keeping track of several serious disorders.
The amount of picture data produced by hospitals annually is enormous. Deep convolution neural networks, which can assist in the detection of numerous patterns in the images, can be trained using these snaps. The interpretation of these images will be aided by artificial intelligence, which will also help with diagnosis and provide doctors with the skills they need to make potentially life-saving choices.
Medical Imaging Areas in AI
Breast Mammography: Radiologists can diagnose breast abnormalities and find malignant cells or tissues with the use of artificial intelligence. Utilizing magnetic resonance imaging (MRI), the software employs Deep Learning-based methods to evaluate and classify breast abnormalities. Radiologists have used imaging methods like Digital Breast Tomosynthesis (DBT) and 3D Mammography to make life-saving diagnoses.
Cardiac MRI: AI assists in the identification and detection of patients who may be having strokes. An artificial intelligence (AI)-based system examines computed tomography (CT) pictures for signs of a possible stroke. Large vascular occlusions (LVOs) are identified in scans using deep learning techniques. Automating sophisticated cardiac analysis is made possible with artery's Cardiac MRI using machine learning and trained models.
Lungs Imaging: Another area where AI has been useful is lung imaging. To identify probable lung cancer, AI-based algorithms examine the lungs and make use of diagnostic imaging like CT scans. A technique known as an Augmented CT screening Solution (AI — CT) was developed by a Chinese startup that can identify possible lung cancer lesions in CT scans.
X-ray: To find arthritis, malignancies, and dental decay, black-and-white images of the human body are frequently created by X-ray devices. While X-rays, which expose people to electromagnetic radiation, have some disadvantages, such as inadequate accuracy in chest inspections that lead to undetected malignancies, including early-stage lung cancer, CT scanning is commonly criticized for its use of ionizing radiation. In certain situations, AI can improve visual interpretation in addition to speeding up testing. To enhance the capabilities of X-rays, Google, for instance, built deep learning algorithms to assist in classifying clinically significant abnormalities on frontal chest radiography.
Benefits of Medical Imaging:
The most frequent issues in the healthcare sector that artificial intelligence addresses are those affecting workload, speed, and accuracy. IoT-based instruments that produce photographs of human bodies and hospital automation systems, as well as Tele-medicine and medication monitors, are all made better by AI in the field of medicine.
Automation: Automated picture registration, anatomical segmentation, and lesion measurement are three ways that AI enhances process automation. In addition, it helps with case interpretation. In certain instances, hiring technicians with radiology degrees is becoming an option rather than a mandate.
Precision: The diagnosis of malignant cells or tumors in eye tissue is made easier with the help of artificial intelligence, which raises diagnostic accuracy by providing algorithms with larger image datasets.
Radiation Exposure: The radiation exposure for patients during CT screening and X-ray tests can be decreased thanks to AI approaches that can precisely recreate high-quality images from low-quality originals.
Future of Medical Imaging With AI:
Before autonomous diagnosis using AI is accepted by healthcare facilities, there is still a long way to go. But everything appears to be going smoothly. To successfully implement AI in medical imaging, trust and reliability difficulties must be handled, which calls for instruction and training. To produce the most accurate diagnosis, radiologists, pathologists, and medical professionals must be able to employ AI in clinical practice, evaluate its efficacy, and understand when to use the appropriate human intervention.
AI-based medical imaging and technology will continue to advance and support incoming radiologists and doctors in making crucial clinical judgments. Thousands of lives will be saved because of its dependability and effectiveness. To progress AI in the field of health, which may be destructive to humans, more study and work are required.
Job Roles in Artificial Intelligence Field:
- Big Data Engineer
- Business Intelligence Developer
- Data Scientist
- Machine Learning Engineer
- Research
- Python Developer
CEOs on Artificial Intelligence
I think about AI as a very powerful tool. What I’m most excited about is applying those tools to science and accelerating breakthroughs.
- Demis Hassbis,
CEO, DeepMind
About the FutureSkills PRIME Programme
FutureSkills PRIME Programme, a joint venture between nasscom and MEITY, primarily aims at Re-skilling/ Up-skilling of IT Manpower for Employability. Various C-DAC centers are involved as the Lead Resource centers for institutionalizing blended learning mechanisms in specific emerging technologies. C-DAC Pune has been entrusted with the responsibility of a Lead Resource Centre for Artificial Intelligence Technology.
Courses run under FS Prime Programme are as below:
1.Bridge course
The course is specifically designed to create awareness of Data Science, Machine Learning, and Deep LearningTools & techniques among participants so that they can recommend and apply these technologies in real life and at their workplaces. The course is meant for graduates, entrepreneurs, interns, fresh recruits, IT professionals, non-IT professionals working in the IT industry, ex- employees, and faculties.
Registration link to enroll for Bridge Course:
2. Training of Government officials (GOT)
Under this program Government Officials will be trained on emerging technologies of AI, which will help them to learn about cutting-edge technologies and upskill to make their work done differently like creating new methods for documentation, near future this would help officials to work in on new government & IT projects which will enable exposure to the futuristic technology world.
3. Training of Trainers (TTT)
Provides an overview of Artificial Intelligence, principles, and approaches with which faculty can enhance their knowledge in the area of AI, Machine Learning, Deep Learning, NLP, Computer Vision, and its application. After completion, of course, Faculty will be able to acquire in-depth knowledge and skills about Artificial Intelligence and should be able to conduct training rest of the courses held under the FS PRIME Programme.
For inquiry w.r.t. TTT & GOT
E-mail: inquiry.fsp.pune@cdac.in
Contact:020-25503114
Written by CDAC Pune