Many activities that people encounter in their daily lives have AI involved. People use, manage, and respond to AI directly and indirectly every hour, minute of the day. Many companies use AI technology to reduce operating costs, increase efficiency, increase revenue, and improve customer experience.
AI in healthcare can greatly improve communication between patients and doctors. One of AI’s greatest advantages is that it increases the ability to process and store large amounts of data. This process is a standardized and integrated process and translates this information into functional tools.
AI has a wide range of healthcare applications. AI is used for cancer treatment. Due to cancer severity and human error, doctors can make overzealous diagnoses that lead to false positive results. This not only drains the patient mentally and physically but waste time.
In the detection of breast cancer, researchers at the Massachusetts Institute of Technology have developed an AI to address this problem. The AI of the team uses machine learning to predict whether previously acquired data will require surgery. The machine used scans of 600 existing high-risk lesions and examined data patterns such as demographics, family history, and medical records to determine which high-risk lesions were likely to require surgery.
Researchers have also shown that AI can more accurately identify skin cancer than dermatologists. The process used by CNN in this research is based on a Google algorithm that allows AI to visually distinguish between thousands of different objects. Dermoscopic images are enlarged, high-resolution images created with a dermoscopy tool. They make diagnoses easier than a naked eye inspection. The widespread integration of AI with dermatological clinical practices in machine learning is likely to increase the detection of skin cancers and improve the results.
AI tools can increase the workflow of radiologists and pathologists, support clinical decision-making, and improve the delivery of care. AI could help overcome several healthcare challenges in the coming years, and it could play a leading role in the functioning of future healthcare systems, ensuring the best use of clinical resources and optimal patient outcomes.