There is a lengthy discussion of Artificial Intelligence and its application in different domains. Global corporations are investing in creating innovative AI applications. Taking a cue from this development, healthcare organizations are looking to apply AI to improve healthcare delivery and deal with intractable health problems. Here are some examples that show how AI will impact the healthcare sector.
More Accurate Cancer Diagnosis
According to experts like Logic Plum, an accurate diagnosis of any ailment or disease is the first step to individualized treatment and faster recovery. Many companies working on AI are focused on creating AI systems that can provide a more accurate diagnosis. The AI-driven application can be programmed to accurately identify signs of diseases in MRI, CT-scans, and X-rays.
Even today, there are several AI-based programs used for cancer diagnosis. These applications process photos of skin lesions for accurate cancer diagnosis.
Intelligent Symptom Checker
The AI-powered Chatbot can listen to patients’ health concerns and symptoms and direct the patient to the right medical care facility based on the diagnosis. It will allow healthcare facilities to treat patients more quickly and allow the staff to focus on providing core medical services like providing patient care.
Blood and urine tests play an essential role in checking symptoms of a particular disease. The AI-programmed system can quickly identify rare objects in blood and urine samples. The medical diagnosis solutions can automatically detect abnormalities in tissues and body fluids.
Optimized Drug Delivery
One of the challenges faced by pharmaceutical companies is delivering samples to doctors. The cost involved in traditional delivery models has increased and is not practical. According to healthcare experts, AI can create and enforce supply chain models that make optimized use of available resources.
The AI-based supply chain model can consider historical data and combine past and existing orders to help pharmaceuticals organize warehouse stocks and reduce shipping costs. The experts like Logic Plum believe AI-based platforms can provide accurate supply chain predicted models that can optimize drug delivery at reduced costs.
Disease Propensity refers to identifying patients who are more likely to suffer from a particular disease in the future. Pre-emptive action is highly valued in healthcare as it allows healthcare providers to manage and cost effectively. AI can be used to build Data Robots that can scan patient data and identify at-risk populations.
The analysis can target marketing efforts to the patient’s concerns by communicating the right information to the patient; healthcare facilities can improve response rates and get better outcomes from the service.
Predicting Patient Readmission Risk
One of the healthcare sector’s challenges is the inability to track a patient’s health after being released from the hospital. The lack of contact with the patients increases health risk and also increases the chances of readmission. The AI-based system can be useful to predict patient readmission risk
The AI-based system can create models based on patient data, including problems faced by patients like chronic disease, lifestyle, habits, and abusive relationships. The data analysis can help the healthcare provider take proactive measures to reduce patient readmission chances.
To sum up, the increased use of big data and analysis will increase AI’s scope in the healthcare industry. As AI technology improves further, you can expect more AI applications used by life sciences companies, providers of healthcare providers, and care seekers.