Artificial intelligence (AI) has been used in multiple sectors over the years, and now it is paving its way into the healthcare sector. AI is not a single technology; rather, it is a set of multiple technologies that include machine learning, natural process learning, expert-based systems, and more.
5 Ways AI Can Be Used In The Detection Of Arthritis
Here are 5 Ways AI Can Be Used In The Detection Of Arthritis.
1. Diagnosis And Early Detection Of AI
AI algorithms can analyze medical images such as X-rays, MRI scans, and CT scans to detect early signs of arthritis. It can help detect it at a very early stage.
- Image Analysis: AI can identify little and minute details and provide a detailed diagnosis of the condition. For example, AI can identify subtle changes in joint structures that might indicate the onset of arthritis before symptoms are clinically apparent.
- Pattern Recognition: AI can analyze large datasets such as patient records, genetic history, and clinical history and develop a dataset that can be useful in predicting the factors responsible for arthritis development. This can help recognize the causative factors and including the lifestyle changes that will help one reduce the risk of arthritis development.
2. Development of Personalized Treatment:
The same treatment regimen might not be applicable to everyone; hence, the development of a personalized healthcare routine can be of much more use.
- Predictive data analytics: AI models can be developed based on the patient's healthcare records, identify the progression of disease, and develop a detailed personalized treatment plan for a particular individual.
- Treatment optimization: By analyzing the data related to the patients, such as age, gender, genetic factors, and lifestyle, AI can suggest personalized treatment plans that can be much more precise and according to the unique characteristics of the patients.
3. Drug Discovery and Development:
Drug discovery and development is a very cumbersome and long process, according to the traditional methods of high-throughput screening.
- Virtual Screening: AI can help screen large sets of data and speed up the process of new drug candidate identification for the treatment of arthritis by screening them virtually based on their structure.
- Target Identification: AI A much more targeted approach can be developed with AI. AI algorithms can help us identify targets of newly developed drugs with the help of available data on various targets in the body on which the drugs act.
In this era of big data, this time can be reduced by developing a much more specific procedure for the identification of new molecules that can be useful in treatment.
4. Patient Management and Remote Monitoring:
AI has enabled us to keep track of the patient’s health and maintain adherence to the drug regimen and exercise routines. Not only does it provide reminders to the patients, but it can also provide information to healthcare professionals regarding the exact condition of the patients in real-time.
- Remote Monitoring: AI-enabled devices can help us continuously track patient information in real time and include any new medication change in the treatment plan for the patient in case of any adverse effect or worsening of the disease.
- Adherence support: AI can provide support and help the patient adhere to the routine by providing personalized reminders and suggesting changes to the patient's regimen according to his condition.
5. Clinical research:
AI can provide great support during clinical research, analyzing data at a much higher speed and speeding up the conclusions.
- Data Analysis: AI can analyze large amounts of clinical data at a much higher speed. It can be useful in analyzing which drug is better responded to by the subjects of the study, optimizing the treatment plan, and enhancing the study design.
- Evidence generation: AI can help us transform existing data into actionable insights that can be used by researchers and drug manufacturing companies to fast-forward their approach.
What AI might not tell you?
- AI aims to make the healthcare system more efficient, precise, seamless, and communicative.
- As much as speeding up the diagnosis is important, it is also important to correctly diagnose the disease so that we may not presume an unhealthy state as healthy.
- AI tells you about all the known diseases, but it cannot tell you about newly evolved diseases as it functions on the available data.
- It can be misleading in terms of diagnosis if it is unable to recognize a symptom that might be complex and may label it as a normal condition due to the lack of data.
- Several factors, such as biases, including racial bias or socioeconomic bias, may be involved in the inaccurate representation of data regarding certain communities.
- For common and well-researched diseases, AI can lend itself to faster, more cost-efficient, personalized healthcare facilities, thereby generating improved patient outcomes.
- Although AI can boost the processes involved in the healthcare system, humans always have their role to play too.
- Humans are aware of a patient’s circumstances, such as their socioeconomic status, emotional state, and agonized state.
- Hence, we can sympathize with the patient and support them.
- Humans need to verify the diagnosis made by AI through traditional methods.
AI can make the healthcare setup more efficient and precise and can speed up the processes involved in diagnosis. Despite all the advantages, we know that AI functions on already-available data, and the data needs to be constantly updated, and regulations are needed to maintain the privacy of patient data.
The involvement of humans remains necessary for the verification of outcomes generated via AI. AI has great potential, and with progressive research and development in AI technology, it can act as a strengthening pillar in the healthcare setup.
Arthritis Overview & Treatment Management Guide
Check 5 step detailed guide on Arthritis Overview & Treatment Management.
Conclusion
Overall, AI holds great promise for transforming the management of arthritis by improving early detection, personalizing treatment approaches, accelerating drug discovery, and enhancing patient care through continuous monitoring and support.
As AI technologies continue to evolve, they are expected to play an increasingly integral role in the fight against arthritis and other complex diseases.
Check Drlogy's Arthritis Overview & Treatment Management Guide for detailed arthritis treatment information and solution related to this diseases.
References:
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- Bohr, A., & Memarzadeh, K. (2020). The rise of artificial intelligence in healthcare applications. Artificial Intelligence in Healthcare, 25. https://doi.org/10.1016/B978-0-12-818438-7.00002-2
- Dang, A., Arora, D., & Rane, P. (2020). Role of digital therapeutics and the changing future of healthcare. Journal of Family Medicine and Primary Care, 9(5), 2207. https://doi.org/10.4103/JFMPC.JFMPC_105_20
- Momtazmanesh, S., Nowroozi, A., & Rezaei, N. (2022). Artificial Intelligence in Rheumatoid Arthritis: Current Status and Future Perspectives: A State-of-the-Art Review. Rheumatology and Therapy, 9(5), 1249. https://doi.org/10.1007/S40744-022-00475-4
- Paul, D., Sanap, G., Shenoy, S., Kalyane, D., Kalia, K., & Tekade, R. K. (2021). Artificial intelligence in drug discovery and development. Drug Discovery Today, 26(1), 80. https://doi.org/10.1016/J.DRUDIS.2020.10.010
- The Role of AI in Personalized Healthcare. (n.d.). Retrieved June 25, 2024, from https://gaper.io/role-of-ai-in-personalized-healthcare/
- Vora, L. K., Gholap, A. D., Jetha, K., Thakur, R. R. S., Solanki, H. K., & Chavda, V. P. (2023). Artificial Intelligence in Pharmaceutical Technology and Drug Delivery Design. Pharmaceutics, 15(7). https://doi.org/10.3390/PHARMACEUTICS15071916
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