Original article was published by BoTreeTechnologies on Becoming Human: Artificial Intelligence Magazine
Why use Python Programming for building a Healthcare App Development
Python is one of the best programming languages used across a plethora of industries. The healthcare sector is a significant benefactor of the language. With Python programming in healthcare, institutions and clinicians can deliver better patient outcomes through dynamic and scalable applications.
Today, healthcare is generating tons of data from patients and facilities. By making the best use of this data, doctors can predict better treatment methods and improve the overall healthcare delivery system.
One of the biggest benefits of Python in healthcare is that it can help in making sense of the data by working with Artificial Intelligence and Machine Learning in healthcare. Python development services is a best option for robust language that allows computation capabilities to derive valuable insights from data that can assist in healthcare applications.
Python healthcare projects must deal with HIPPA compliance that comes in handling healthcare data. While it doesn’t matter which programming language or framework you use for healthcare apps, Python is a safe option as it has in-built tools that offer complete security.
Today, Python for healthcare is used primarily in Machine Learning(ML) and Data Science applications that elevate patient outcomes. ML algorithms enable healthcare analytics using Python as developers can build health monitoring and tracking applications.
Python benefits in Healthcare: How it helps
You may ask,” How is Python used in healthcare?” Since it is a programming language, it can never directly offer any advantage. However, the primary Python benefits in healthcare occur from its usage in the application that supports the medical and health system.
Python is an open-source language that allows building innovative healthcare solutions that can deliver better patient outcomes and lead to improved care delivery. Python complies with the HIPPA checklist for ensuring medical data safety.
On the other hand, Python code for healthcare is powerful enough to deliver the desired level of performance that patients and clinicians need. Robust and dynamic apps are more convenient for stakeholders, and Python is one of the best programming languages used in healthcare for that purpose.
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Here’s how Python functions are used in the operations of healthcare:-
- The most significant benefit of Python programming in healthcare is predictive analytics for diseases. Developers can efficiently use Python for building Machine Learning models that can predict diseases before they get severe.
- Predicting how any disease will turn out is also a challenge. Today, most systems are inefficient in identifying what would happen next. With the help of healthcare data analytics using Python, doctors can predict the right treatment plan or mortality based on the EHR data.
- For example, Google’s Deep Learning and Machine Learning algorithm enables detecting cancer in patients using their medical data and history. It speeds up the process of treatment so that clinicians can avoid any serious complications that may occur in the future.
Want to know how Machine Learning can improve healthcare outcomes? Read this blog to know more.
- Diagnostic errors are one of the most common mistakes in the healthcare industry. A significant portion of patient deaths occurred due to a mismatch in diagnostics. Python healthcare projects that involve the applications of data science can help make an accurate diagnosis through image analysis.
- Machine learning models can go through MRIs, ECGs, DTIS, and many more images quickly to identify any pattern of disease that may be shaping up in the body. Healthcare data analysis Python shows a perfect representation of the body’s inner workings.
- While the traditional image-based diagnostics offered multiple images that might get hard to interpret, Python code for healthcare helped in building algorithms that generate a single image for presenting the diagnosis.
Better patient management
- Managing patients can consume a lot of time. Healthcare facilities with limited staff cannot take care of the patients, appointments, treatments, all at once. Healthcare application development enables the facility to adopt a more technological approach to managing patients such that the staff has more time for critical activities.
- One of the Python benefits in healthcare is an application where patients can schedule and reschedule appointments, get answers to common queries, order their medications, emergency contact with clinicians, and update their health data.
- This holistic approach of patient management will provide staff with the time that they can spend on treating patients with a critical illness. A Python healthcare application will be scalable, dynamic, and user-friendly, so it becomes easier for the stakeholders to use it.
- Any healthcare application will need a secure programming language that can showcase its capability and securely handle patient data. It acts as additional support for healthcare facilities that allow the entire system to function in a more efficient manner.
Resource: Top 5 Healthcare App Development Trends
Why is Python the perfect programming language for Digital Health Solutions?
Python programming in healthcare has several benefits that healthcare facilities cannot ignore in today’s world. Along with its frameworks like Django and Flask, Python offers multiple advantages that can lead to better healthcare outcomes.
Python is a dynamic programming language that enables building feature-rich web app development and mobile applications. With the progress of mHealth, Python healthcare projects have grown twofold. Today, healthcare institutes and clinicians want to personalize the patient experience through high-quality web apps.
Apart from that, wearable gadgets allow users to update their health data online so that healthcare facilities can easily access it. Keeping track of health has become possible because of Python programming in healthcare. The apps that connect with these wearable devices need a robust language that can support efficient operations, and Python is the way to do that.
Here are a few benefits of Python for web and mobile applications for elevating healthcare outcomes:-
- Readability: Python is one of the programming languages used in healthcare that has a clear and easily readable syntax. Even for adding complex functionalities, developers can write simple code or add plugins for making it feature-rich.
- Scalable: The biggest Python benefits in healthcare is that it is a highly scalable programming language. Healthcare facilities may have tons of data and heavy traffic load from countless patients. Python doesn’t lag or break down when dealing with massive data and information.
- Libraries & Community: Python has a plethora of libraries that developers can use to add features in the mHealth application. They don’t need to write code for every attribute as there is some library available that can help in doing that.
Also, Python projects in healthcare benefit from the wide community that provides solutions to all the problems that may occur. The developers have already provided answers to a lot of common Python queries that may hinder the development process.
Python has multiple use cases in healthcare and other apps as well. Here’s a detailed article for you.
Get the help of experts for Healthcare Application Development
Python is not only an excellent programming app for Django web development but also a great choice for healthcare mobile applications as well. When you talk about Machine Learning in healthcare, Python comes up as the clear winner.
Machine Learning and Artificial Intelligence are changing the game in healthcare. From early diagnostics to predicting the right treatment path, data science has truly changed how we approach healthcare. It always helps to hire experts in Python development services for building a healthcare application.
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Why use Python Programming for building a Healthcare Application was originally published in Becoming Human: Artificial Intelligence Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.