In the digital era that we live in, many aspects of our lives have been taken over by mobile phones and computers. Software, technology, and coding have become essential aspects of every industry. And the healthcare industry is no exception to it.
How medical professionals and practitioners own, access, and maintain healthcare data has witnessed a digital shift – from paper to electronic formats. As a result, healthcare institutions have been able to generate and gather a large amount of data.
Medical institutions and facilities have witnessed a recent adoption of Python development services to combat the various challenges in healthcare.
Python in healthcare industry is being used by data scientists as it offers several tools that can generate data-driven insights for healthcare professionals.
Medical practitioners can employ Python in healthcare industry to improve the quality and procedure of patient care and healthcare delivery to improve prognosis.
Hospitals and medical institutions need to employ Python development services to maximize insights and output gathered from data, analyze the data, process it, and convert it into understandable and reliable information for healthcare professionals and patients.
By leveraging Python-based AI solutions, the healthcare industry can deliver custom healthcare solutions and provide better patient care.
The Role of Python in Healthcare Industry
The main application of Python in healthcare industry is based on Machine Learning (ML) and Natural Language processing-based (NLP) algorithms that conduct various tasks such as image diagnosis, processing medical documents, predicting diseases using human genetics, and various other tasks.
1. Python for Image Diagnostics
ML can conduct analysis of multiple images like Magnetic Resonance Imaging (MRI), Computerized Topography (CT) scans, and Diffusion Tensor Imaging (DTI) scans to process them and provide the patient diagnosis.
Using Python as a programming tool, a series of instructions can be sent to an AI model that further uses Machine Learning to scan those images. These images provided by Python-based ML algorithms are able to process multiple pieces of information to convert them into a single diagnostic outcome.
This data gathered through image analysis is accurate up to approximately 92%. This rate of accuracy can be further enhanced with the intervention of pathologists to vet the data.
2. Python for Detecting Tumors
ML-based algorithms can be used to detect tumors by using Computer-Automate Detection (CAD) scans. By using this technology, healthcare professionals are able to ascertain the probability of a detected lesion; whether or not it is indeed a lesion.
The technology works as a second opinion for radiologists and improves the accuracy of screening and at the same time, mitigates the cost that would have been incurred in getting a second opinion from another medical professional.
Deep Learning solutions based on employing Python development services offer another major advantage to healthcare institutions.
Physicians face a major challenge in detecting glioblastoma, which is a type of brain tumor. The tumor is hard to detect and locate which makes it difficult for medical professionals to provide timely treatment.
Python in the healthcare industry can be used to develop Deep Learning algorithms that automate the assessment of glioblastoma MRIs and facilitate timely detection and treatment of tumors.
3. Python for Detecting Cardiovascular Abnormalities
Python-based AI/ML algorithms use images like chest X-rays of patients who are experiencing symptoms such as shortness of breath to detect heart abnormalities among patients. Python-powered AI tools can help in automating the assessment of the patient’s health condition to predict and treat cardiovascular diseases among patients.
Additionally, ML algorithms can assess these images and generate reports based on them to detect abnormalities.
4. Python for Determining Injuries
Python is used to develop ML tools that data scientists utilize to identify injuries and fractures. Medical professionals and surgeons can use these tools to detect injuries and dislocations that are difficult to detect in order to provide the best treatment.
Furthermore, these AI tools are useful in generating timely and accurate reports of medical image analysis that assist healthcare institutions in mitigating patient risk.
5. Python for Cancer Screening
Medical imaging technology is used by Oncologists for the preventive detection of Cancer through routine screenings. These screenings help them determine if the patient is at risk of tumor and if so, classify whether the tumor is malignant or benign.
This helps combat the error of false positives that lead to unnecessary testing and treatment. AI can enhance the accuracy of medical image reading, which assists healthcare institutions decrease the rate of benign biopsies.
6. Python for Predicting the Onset of Psychosis
Python-based Natural Language Processing algorithms can be leveraged to conduct Latent Semantic Analysis, a technique that is capable of predicting whether or not, a patient is likely to develop psychosis.
7. Python to Improve the Patient Experience
Hospitals and medical institutions can employ Python development services to augment the patient experience. Using Python to build healthcare applications empowers healthcare institutions to effectively manage patients, treatments, schedule patient appointments, and reducing administrative workload.
Further, with the help of AI-based virtual assistants, patients can get answers to their queries and commonly asked questions such as requesting a refill on a prescription, etc. This allows the medical staff to direct more time toward treating patients with critical illnesses.
8. Python to Enhance Operational Workflow
Python-based automation can help hospitals and healthcare institutions optimize their operational workflow. Python-backed automation tools can perform repetitive administrative and operational tasks without any human intervention.
This frees the healthcare staff to pay attention and dedicate their time to more urgent, complex tasks.
9. Python for Drug Discovery
Python can be effectively used for drug development and is in fact, a leading programming language used for drug discovery.
For instance, AstraZeneca is a pharmaceutical company that leverages PyMOL, a Python tool to speed up its drug discovery process. The PyMOL tool helps display target diseases using 3D structures.
It also has around 12 different modes of visualization using which, users can highlight and separate different structural features among targets.
Moreover, the tool is designed in a manner that can adjust well to the changing prediction methods and efficiently comb through large data sets to design prototypes of drugs.
Leveraging Python Development Services for Predictive Analytics
Python-backed Machine Learning algorithms enable healthcare professionals to conduct predictive analytics to predict diseases and establish its cause among patients.
Predictive analytics allows healthcare professionals to attain insights into the patient’s health to provide custom healthcare solutions such as changing the patient’s healthcare plans to mitigate his/her risk of developing complex diseases.
The benefits of AI in healthcare
Whether it is accelerating the pace with which medical research is conducted or enabling clinicians to improve their decision-making and diagnosis of treatment, employing AI in healthcare offers several benefits to both, the healthcare institutions and the patients.
Take a look at how healthcare institutions can employ AI through Python development services and enhance patient care delivery and outcome.
a. Early disease detection and diagnosis:
Python-based Machine Learning models can be used to monitor patient symptoms to detect risks by collecting patient data through medical devices such as wearables. This data is then shared with the patient’s medical professional to alert them in case of risk to the patient’s health.
b. Patient-specific treatment:
AI models are able to learn and preserve references to offer custom healthcare solutions to patients in real-time. Healthcare institutions can also employ an AI-based virtual assistant to help solve patient queries and deliver solutions based on the medical history, preferences, and personal needs of the patient.
c. Enhance clinical trial efficiency
Based on the outcome of clinical trials, patients are assigned medical codes. AI-based technology can help enhance the process of clinical trials by offering a faster search for these medical codes assigned to patient outcomes.
d. Reduce the cost of drug development
AI can be employed to improve drug design and to create combinations during drug development. This significantly reduces the cost of developing newer drugs.
e. Reduce Diagnostic errors
As seen above, AI solutions based on Python programming play an important role in the medical imaging process. They can be used to detect early signs of breast cancer or other health conditions.
An Outlook on the Future of AI in Healthcare
The healthcare industry handles large amounts of complex data on a daily basis which needs to be processed and analyzed by healthcare institutions.
With a growing expansion of both the volume of data handled and its complexity, healthcare institutions need to develop AI/ML-powered applications that can propel timely and efficient delivery to patients.
The future of AI in healthcare in the coming years is anticipated to be witnessed through hybrid models powered by AI/ML algorithms that will lend support to clinicians to conduct diagnoses, plan treatments, identify and detect risk factors, and many such things that optimize patient care delivery.
This will in turn enable healthcare providers to offer improved patient care, enhance operational efficiency, mitigate risks, and deliver outstanding patient care.
Streamline Hospital Operations With Python-Based AI Models
The implementation of Python in healthcare industry is equally challenging and effective. When implementing Python-based solutions in the healthcare industry, however, it is important to ensure that issues like data protection or third-party legitimacy do not arise.
By employing AI/ML algorithms, data scientists have been able to utilize data-driven insights generated by these algorithms to transform healthcare through predictive analytics and personalized medicine.
Using Artificial Intelligence algorithms, data scientists and Machine Learning specialists have been able to reduce costs and improve the quality of life of billions of people worldwide by using AI algorithms.
Healthcare institutions need to collaborate with the best healthcare software development company to deliver effective patient care.
Offering industry-best Python development services, Quixom’s team of Python experts leverage Python programming language to build AI/ML solutions that deliver exceptional healthcare solutions and enhance the patient experience.
By collaborating with us, you can build, develop, and deploy top-notch healthcare software solutions that revolutionize patient outcomes, workflow management, and care delivery.