Elevating Healthcare with Python: The What, Why & How

The healthcare sector has benefited tremendously from advancements in technology. Professionals in healthcare have adopted technology to enhance patient experience, digitize records, and leverage data effectively. A technology that deserves special mention here is Python. Healthtech companies are using Python to build high-impact solutions that address their most pressing issues. Data scientists are counting on the programming language to generate insights that improve operational efficiency and decision-making.

So, what sets Python apart as a favored choice within healthcare? Industry experts describe Python as an easy-to-use language. It has a clear syntax and a small learning curve. This means developers are able to write and implement code quickly, reducing the time spent on fixing bugs and other issues. Also, Python provides a range of libraries and frameworks. These aid in the development of feature-rich, scalable applications that improve the quality of care delivered to patients.

What Makes Python Standout in Healthcare

• Easy to Learn: Python is a language known for its simplicity and readability. Its syntax is intuitive and resembles the English language. Developers who have little or no coding experience often choose Python as their first programming language.

• Flexible: A general-purpose programming language, Python is highly flexible. From web development and data analytics to machine learning and artificial intelligence, Python is used almost everywhere. This also explains why Healthtech players are hiring Python developers in such large numbers.

• Active Community Support: Python has been there for around 25 years, which explains why it has a robust user community. The Python community has created guides, documentation, and tutorials for developers to refer to when they face issues during coding.

• Suited for Data Analytics: Python’s popularity in the realm of data analytics stems from its effectiveness in this field. The programming language excels in data analysis and is supported by frameworks tailored for handling data. This makes it a top choice for healthcare data scientists.

• Compatible with IoT: IoT devices allow healthcare professionals to monitor patient health and ensure their well-being. Many of these devices support Python or its scaled-down version, Micropython.

Top 4Use Cases of Python in Healthcare

1. Predictive Analytics: Predicting how a disease will progress is often difficult for healthcare professionals. The healthcare fraternity leverages Python-driven models to provide faster, more accurate disease predictions. This helps doctors plan more personalized treatment for any patient.

Python-based models use a patient’s Electronic Health Record (EHR) to predict how long a patient with a life-threatening illness will survive. The EHR containing information related to a patient’s diagnosis and prescriptions is connected to a Deep Neural Network (DNN) built using Scikit and PyTorch. The predictions of the neural network help doctors figure out when they should bring in palliative care for any patient.

Python’s machine learning models are also used to learn how a patient’s genetic makeup might affect the progression of their disease. This way, doctors may modify their treatment plans and minimize complications.

2. Image Analysis: In image analysis, technologies like X-ray, ECG, and MRI are employed for detecting an array of health conditions. Radiologists rely on images and scans generated through these tests to manually diagnose ailments.

Healthcare professionals employ Python-based machine learning algorithms for image interpretation and analysis. These algorithms detect irregularities not apparent to the human eye.

For instance, machine learning helps detect early-stage breast cancer from mammograms. It’s also used in diagnosing neurodegenerative conditions like Alzheimer's disease through MRI scans. These models are capable of spotting heart conditions by analyzing ECG results. Timely and accurate diagnoses ease the burden on healthcare professionals and improve patient care quality.

3. Hospital Management: Healthcare institutions face challenges in operating efficiently due to increasing workloads and limited staff resources. Managing information, scheduling appointments, and handling consultations manually gets overwhelming at times. Python comes to their rescue by empowering healthcare providers with top-notch applications that simplify operations.

Python’s powerful libraries and frameworks help build patient management applications that send automated reminders to patients. This minimizes patient no-shows. Python-based applications also streamline insurance claims processing by ensuring accurate, timely payments to the policyholders. As a result, healthcare professionals are able to eliminate mundane tasks from their work, focusing on providing superlative patient care.

4. Drug Discovery: Drug discovery is always complex and time-consuming. A major challenge in drug development is finding a suitable target molecule to which the drug could bind and work effectively. Python-based AI models analyze large data sets to identify and validate an appropriate target. This eliminates a lot of back and forth required during experimentation. AI also helps convert the data generated during clinical trials into written content that is submitted to authorities for review. This speeds up drug discovery and development.

Wrapping up

The need for providing high-quality patient care while reducing operational costs has made Python relevant in the healthcare industry. Healthtech players are increasingly hiring Python developers to build applications that simplify administrative work, uncover meaningful patterns and insights, and mitigate the burden on healthcare workers. The future of Python in healthcare looks bright, considering its versatility and suitability for a range of use cases in the domain.