Pratiti Technologies

Category: Health Care

  • Personalizing Healthcare with Generative AI

    Personalizing Healthcare with Generative AI

    Table of Content:

    Introduction
    How can physicians benefit from Generative AI-based healthcare software? Here are some clear use cases:
    How physicians can adopt Generative AI
    Here’s a closer look at how LLMs can transform healthcare use cases – and how to implement them.
    Here are some of common use cases where LLMs can benefit physicians and healthcare providers:
    How Databricks can help get started with LLMs
    How Pratiti Technologies can help in personalizing healthcare

    Introduction

    Healthcare is changing. More patients expect personalized care. Healthcare providers are focusing on patient experience as well as quality of care. Also, more physicians and medical practitioners are facing burnout due to increased work pressure. The American Osteopathic Association reveals nearly 50% of physicians experienced burnout in 2024. A recent survey found that 50% of the physician’s time is spent on administrative work like updating electronic health records (EHRs). Even during patient engagement, physicians spend 52.9% of their time in EHR-related activities.

    With the emergence of Generative AI, healthcare professionals are wondering whether they can personalize patient care – without increasing their workload. Thanks to its ability to tap into massive healthcare data, can Generative AI enable personalized care

    How can physicians benefit from Generative AI-based healthcare software? Here are some clear use cases:

    1. Patient Diagnosis

    Generative AI can analyze data points from any patient’s medical history or health records to deliver an accurate diagnosis.

    Additionally, Generative AI can help physicians diagnose medical images more accurately. For instance, using the image segmentation technique, Generative AI algorithms can automatically segment medical images (for example, MRI or CT scans) into various regions of interest. This is more effective for diagnosis of tumors or lesions than manual segmentation.

    IBM’s Watson Health technology applies AI and data analytics to analyze patient records including their:

    • Medical history
    • Genetics
    • Symptoms

    Another published study on Watson Health’s AI-based decision support system recorded a 93% concordance rate with treatment recommendations from an expert panel of doctors.

    2. Administrative Work

    As mentioned earlier, healthcare practitioners spend a lot of time in administrative work such as documenting medical records and scheduling appointments for patients. By adopting Generative AI, healthcare software solutions can automate administrative work so that physicians can focus on delivering patient care. By using AI technology for dictations and medical scribes, physicians can now spend more time with patients, thus enabling personalized care.

    AI-powered tools can generate clinical notes from doctor-patient consultations and manage the billing process. One example is that of the AI-enabled Zocdoc platform used for booking doctor’s appointments.

    3. Medical Research

    Among other use cases, Generative AI has the potential to advance medical research and innovations. For instance, medical researchers can leverage Generative AI to generate synthetic data based on patient cohorts. This enables them to simulate various scenarios for clinical trials and evaluate the efficacy levels of their treatment.

    Besides, AI-powered tools can help research work by preparing interview scripts and research briefs for medical teams. With AI-powered transcription during user sessions, researchers can focus on the user’s non-verbal communications and reactions to make accurate decisions.

    4. Predictive Medicine

    With the use of Generative AI, physicians can also identify individuals at maximum risk from diseases or chronic conditions. Through predictive medicine, they can personalize the disease prevention plan for each patient, thus delivering an early-stage intervention to stop the onset of the health problem.

    Further, Generative AI tools can analyze vital health indicators from personal wearables. This includes indicators like heart rate, stress levels, and blood glucose levels. Generative AI algorithms can identify data patterns from patient records and accurately predict the trajectory of diseases.

    How physicians can adopt Generative AI

    What’s the best way for healthcare professionals to create Generative AI models for various use cases? There are 3 possibilities:

    ● In-house Development

    This option is feasible if the healthcare company has the necessary technical expertise to build AI models. Through this option, they can also customize the AI model to suit their applications and use cases.

    On the plus side, in-house development enables companies to have complete control over their development process. Internal teams also have a better understanding of the project requirements and can easily collaborate with other stakeholders. On the flip side, in-house development is expensive due to high hiring and training costs.

    ● Buy

    This is a feasible option for generic or industry-specific use cases. These AI-powered solutions are cost-effective and built with the vendor’s industry expertise.

    Among its advantages, industry-specific solutions are backed by industry experts. Hence, these solutions often meet industry-specific needs and standards. Additionally, companies incur a lower upfront cost when buying these solutions. Among the disadvantages, these solutions cannot be customized to specific business requirements—or can incur high customization costs. Additionally, they may include a host of features (or functionalities) that are not useful to the purchasing company.

    ● Outsourced Development

    Healthcare professionals or companies can outsource their AI development to external AI experts. This provides them access to customized AI solutions tailored to their needs and processes in a quick time.

    As compared to in-house development, outsourcing is more cost-effective as it allows companies access to technical knowledge and expertise without any hiring process. On the flip side, healthcare companies have lower control over the development process. Besides, external solution providers may not fully comprehend business objectives or may not have the necessary industry experience to undertake this project.

    Here’s a closer look at how LLMs can transform healthcare use cases – and how to implement them.

    Transforming Healthcare using LLMs

    The growing popularity of large language models (LLMs) like ChatGPT is fueling the expanded use of AI and data in the healthcare sector. On their part, LLMs can transform healthcare by:

    • Automating medical coding and patient billing.
    • Detecting any medication errors.
    • Improving medical documentation.

    Here are some of common use cases where LLMs can benefit physicians and healthcare providers:

    • Patient engagement

    Healthcare providers are deploying AI-powered chatbots or virtual assistants to improve patient communication and engagement. This can easily be integrated into the physician’s or healthcare company’s website or mobile app. LLMs can automatically summarize and provide appropriate responses to a patient’s queries.

    • Reduced documentation

    Clinical documentation and medical transcriptions are both costly and time-consuming for physicians. By analyzing patient records from EHR, LLMs can reduce documentation and improve decision-making by identifying data patterns

    • Access to scientific literature

    LLMs can also boost medical research by enabling researchers to stay updated on the latest medical studies and research findings. LLMs can process and summarize massive volumes of scientific literature to present accurate hypotheses.

    • Drug approvals

    LLMs can accelerate drug approvals and reduce development costs. For instance, LLMs can select the right population sample for conducting clinical trials and accelerate patient recruitment. Similarly, drug researchers can utilize LLMs to generate report summaries for faster regulatory approvals.

    How Databricks can help get started with LLMs

    As a data intelligence platform, Databricks enables healthcare professionals to unlock the potential of healthcare-related data. With its scalable and collaborative platform, Databricks can analyze massive volumes of data – collected from diverse sources including EHRs and medical images.

    With Databricks features like Unity Catalog and Clean Rooms, healthcare companies can safely share healthcare data with a host of medical researchers and healthcare providers.

    Here’s how healthcare professionals can leverage Databricks platform to implement LLM:

    1.Create a comprehensive data strategy.

    The first step is for healthcare providers to determine the desired outcome from using LLMs. Based on this factor, they can choose the right data sources and the technology for achieving this outcome. For example, how to use Generative AI models to personalize patient recommendations.

    2.Democratize the healthcare data.

    The next step is to build a unified data architecture to store and analyze various types of healthcare data. By capturing and labeling data, healthcare providers can enable patient outcomes. To maintain compliance in data sharing, Databricks provides efficient governance and accountability.

    How Pratiti Technologies can help in personalizing healthcare

    Among the leading healthcare software development companies in India, Pratiti Technologies is enabling healthcare companies to deliver personalized care and services. Our managed services are facilitating Generative AI tools across healthcare functions.

    Our Data + AI experts can help you leverage data-driven capabilities in your medical practices. If you want to learn more, contact us today!

    Our Services

    Data Analytics Solutions | Healthcare Software Development | Cloud Computing Services Providers | Edge Computing Platform

    Nitin
    Nitin Tappe

    After successful stint in a corporate role, Nitin is back to what he enjoys most – conceptualizing new software solutions to solve business problems. Nitin is a postgraduate from IIT, Mumbai, India and in his 24 years of career, has played key roles in building a desktop as well as enterprise solutions right from idealization to launch which are adopted by many Fortune 500 companies. As a Founder member of Pratiti Technologies, he is committed to applying his management learning as well as the passion for building new solutions to realize your innovation with certainty.

  • How AI Is Making Personalized Healthcare a Reality

    How AI Is Making Personalized Healthcare a Reality

    Table of Content:

    Introduction
    The State of Personalized Healthcare in 2025
    How Pratiti Technologies Can Help in Personalizing Healthcare

    Introduction

    Artificial intelligence is no longer just a buzzword in healthcare it has become the engine powering truly personalized care at a scale. From hospitals to health-tech innovators, organizations around the world are leveraging AI to revolutionize diagnostics, accelerate drug discovery, tailor treatment plans, and enable proactive, data-driven care delivery. What was once a future promise is now a present-day imperative.

    The future of healthcare is one where AI doesn’t replace the doctor it empowers them. By combining real-time data, predictive analytics, and individual patient profiles, AI enables healthcare providers to deliver care that is not only efficient but also tailored to each patient’s genetic, physiological, and lifestyle profile.

    The State of Personalized Healthcare in 2025

    Here’s how AI is redefining what’s possible in healthcare:

    1. Predictive and Preventive Healthcare AI models in 2025 are becoming adept at predicting diseases before they manifest. Algorithms trained on millions of health records can detect early signs of chronic diseases such as diabetes, cancer, or cardiovascular conditions—sometimes months or even years before traditional diagnostics.
    2. Genomics and Precision Medicine The integration of AI with genomics is revolutionizing personalized medicine. By analyzing genomic data, AI tools can identify mutations, recommend targeted therapies, and forecast how a patient might respond to certain treatments. This precision is drastically reducing adverse drug reactions and increasing treatment efficacy.
    3. AI-Powered Drug Discovery Generative AI platforms like Insilico Medicine and Google DeepMind’s AlphaFold are accelerating the drug discovery process. These tools help researchers simulate molecule interactions and develop customized compounds in a fraction of the traditional R&D time.
    4. Virtual Health Assistants and Care Bots From symptom checkers to mental health chatbots, AI is powering virtual assistants that guide patients through their care journey 24×7. These assistants learn and adapt over time, delivering hyper-personalized advice and reminders.
    5. Medical Imaging and Diagnostics AI algorithms are now outperforming human radiologists in detecting conditions like breast cancer, lung nodules, and diabetic retinopathy. Tools like Aidoc and Zebra Medical Vision offer near real-time diagnostics, improving decision speed and accuracy.
    6. Personalized Wellness and Remote Monitoring Wearables paired with AI models provide continuous feedback on vital signs, activity levels, and sleep. This data is used to personalize diet, fitness, and medication plans, helping people manage chronic illnesses from the comfort of their homes.
    7. Federated Learning and Privacy-Preserving AI With growing concern over data privacy, technologies like federated learning are gaining momentum. They allow AI models to be trained on decentralized patient data without it ever leaving the hospital’s servers ensuring compliance and trust.

    How Pratiti Technologies Can Help in Personalising Healthcare

    Among the leading healthcare software development companies in India, Pratiti Technologies is enabling healthcare companies to deliver personalized care and services. Our managed services are facilitating Generative AI, predictive analytics, and real-time decisioning tools across multiple healthcare functions.

    With strong expertise in integrating data from EMRs, wearables, IoT devices, and cloud-native platforms like Databricks, our solutions enable:

    • Patient-level treatment customization
    • Real-time health monitoring dashboards
    • AI-based medical imaging analysis
    • Virtual health assistants with LLMs
    • Predictive modeling for chronic disease management

    Our Data + AI experts can help you leverage data-driven capabilities in your medical practices. If you want to learn more, contact us today.

    📩 insights@pratititech.com  🌐 Visit our website

    Explore our previous insights on this topic: Personalizing Healthcare with Generative AI

    Our Services

    Data Analytics Solutions | Healthcare Software Development | Cloud Computing Services Providers | Edge Computing Platform

    Nitin
    Nitin Tappe After successful stint in a corporate role, Nitin is back to what he enjoys most – conceptualizing new software solutions to solve business problems. Nitin is a postgraduate from IIT, Mumbai, India and in his 24 years of career, has played key roles in building a desktop as well as enterprise solutions right from idealization to launch which are adopted by many Fortune 500 companies. As a Founder member of Pratiti Technologies, he is committed to applying his management learning as well as the passion for building new solutions to realize your innovation with certainty.
  • The Internet of Medical Things – Opportunities, Applications, and Solutions

    The Internet of Medical Things – Opportunities, Applications, and Solutions

    Table of Content:

    Introduction
    IoMT Market Growth
    Benefits and Applications
    Complexities and Challenges
    The Role of a Partner

    Introduction

    Patients and healthcare organizations alike rely today on a magnitude of medical devices to monitor and track critical health metrics. But many of these devices operate in silos, with little or no provision for information exchange. Critical data, when not shared across the ecosystem, can result in life-threatening gaps in the healthcare continuum.

    This is where the Internet of Medical Things (IoMT) comes into the picture. As a collection of medical devices and applications that connect to healthcare information technology systems, IoMT is set to power the new healthcare economy! Several new IoMT apps and devices are being launched every single day. These devices are completely transforming the way healthcare is delivered and consumed.

    IoT-enabled glucometer apps, for instance, deliver real-time glucose, temperature, and other contextual data. They can also monitor parameters such as  food intake, physical activity, and medication, allowing for self-management of diabetes while also facilitating communication between patients and doctors. Abbott Freestyle Libre 2 offers a wide array of on-demand glucose monitoring capabilities, enabling people to live life freely and on their own terms.

    Similarly, IoT-based patient monitoring systems collect patient information such as heart rate, blood pressure, and more. Doctors can easily monitor this data using a central console, enabling the remote monitoring of ICU Patients without any manual intervention. Cogniteq’s patient management software seamlessly monitors cardiac conditions, enabling doctors to make a more accurate diagnosis.

    Read on as we delve into the many opportunities IoT in healthcare, its applications, and solutions.

    IoMT Market Growth

    According to analysts, the global Internet of Medical Things market is projected to grow to $187.60 billion in 2028, at a CAGR of 29.5%. While the COVID-19 pandemic kickstarted the IoMT trend, powering the delivery of virtual care, the continued growth is being driven by several factors, including:

    • The rise in the number of patients with chronic diseases who need continuous, around-the-clock monitoring.
    • The demand for virtual consultation and telemedicine, especially from patients residing in rural areas with little or no access to physical care.
    • The pressure on healthcare institutions to proactively understand patient health and deliver value-based care.
    • Rapid advancements in the telecommunication sector, such as the introduction of 5G, offer several promises for the IoMT industry to flourish.
    • Rising healthcare costs are also driving the IoMT market, especially as patients get increasingly concerned about their health.

    Benefits and Applications

    IoT in healthcare or IoMT presents a paradigm shift in the way healthcare is delivered. It enables efficient real-time, machine-to-machine communication between critical healthcare devices, delivering several benefits.

    From improved remote patient monitoring to tracking medication, connecting ambulances en route to medical facilities to analyzing wearable health data – IoMT improves healthcare professionals’ decision-making capabilities.

    • Remote patient monitoring devices allow providers to monitor and manage patients’ chronic conditions. They encourage patients to take control of their health while enabling doctors to gather vital health information and detect anomalies in time.
    • Medical imaging systems can streamline the transfer of critical medical images within the healthcare network. By continuously processing and monitoring data, these systems can help radiologists diagnose issues and link them with patients’ medical histories.
    • Infusion pumps can improve the precision delivery of medication while allowing doctors to monitor and control dosage over the Internet. Doctors can set, modify, or stop the infusion based on patients’ vitals and keep a record of all the commands for future inspection.

    Complexities and Challenges

    IoMT, although extremely beneficial in today’s digital era, also comes with several complexities in implementation and management. Let’s look at the top 5 challenges of IoMT:

    • High implementation costs: The high cost of IoMT implementation is a major factor that can hamper market growth and deployment success. Costs associated with installation, software updates, hardware maintenance, and network management can be extreme.
    • Cybersecurity risks: Advanced technology invariably poses the threat of cybersecurity. As healthcare institutions look to exploit the capabilities of IoMT, the challenges brought about by the widespread collection and analysis of sensitive patient health data are many.
    • Interoperability hurdles: IoMT demands deep integration with a diverse set of devices, systems, and platforms from different manufacturers. Ensuring seamless communication and data exchange between these devices can be difficult due to differences in data formats, communication protocols, and standards.
    • Data management challenges: IoMT devices generate humongous amounts of data every second. Gathering, storing, securing, and processing this data requires skilled expertise and a strong focus on data security and integrity.
    • Bandwidth and latency issues: Healthcare organizations that rely on IoMT devices need to act on insights in real-time. However, sluggish internet connections and overburdened networks can lead to several bandwidth and latency issues that can impact the accuracy and timeliness of healthcare delivery.

    The Role of a Partner

    From hospitals to post-patient care providers, medical instrument manufacturers to clinical labs, hospitals to medicine providers, organizations across the care lifecycle can benefit immensely through the adoption of IoMT. But as these healthcare providers embrace IoMT for its many benefits, an expert technology partner can help streamline its implementation. Offering the perfect combination of technological innovation and process conversion, a skilled partner can minimize operational costs while improving patient care. A competent and proficient partner can enhance outcomes in every aspect of the healthcare lifecycle, right from consulting to care delivery, deployment to post-implementation support, a partner can:

    • Establish cross-device connectivity across the medical ecosystem and unleash the seamless flow of data from IoT-based healthcare records and systems to patients interacting with care teams at any time and from anywhere.
    • Combine the power of analytics, automation, and intelligence to spark transformation.
    • Help conduct a comprehensive cost-benefit analysis and ensure healthcare providers get maximum returns from their IoMT investments.
    • Establish the right data protection policies and cybersecurity controls and ensure the continued success of IoMT.
    • Reduce implementation and integration complexity, improve efficiency, and empower healthcare decision-makers with actionable insight at the point of care.
    • Harness the potential of healthcare data analytics and improve healthcare decision-making.
    • Invest in robust data management systems to manage the surging volumes of critical medical data efficiently and securely.
    • Promote interoperability through the establishment of the right APIs and integration parameters.
    • Ensure the seamless scalability and upgradability of IoMT implementation while establishing clear regulations and standards.

    As expectations from the healthcare industry increase, the IoMT market is surging globally. IoMT can lead to improved patient care, enhanced healthcare outcomes, and a more efficient healthcare system. But to overcome the challenges that IoMT brings and to realize its full potential, it is important to engage with a skilled and qualified technology partner.

    Watch our webinar on “Crossing the IoT Chasm” to learn more about the different aspects of IoT, understand its various industrial use cases, and evaluate its business impact.

    As a unique custom healthcare software development and technology services company, Pratiti Tech continually strives towards helping organizations achieve healthcare digital transformation goals. Explore our healthcare industry services today and streamline your IoMT journey!

    Our Services

    Data Analytics Solutions | Healthcare Software Development | Cloud Computing Services Providers | Edge Computing Platform

    Nitin
    Nitin Tappe

    After successful stint in a corporate role, Nitin is back to what he enjoys most – conceptualizing new software solutions to solve business problems. Nitin is a postgraduate from IIT, Mumbai, India and in his 24 years of career, has played key roles in building a desktop as well as enterprise solutions right from idealization to launch which are adopted by many Fortune 500 companies. As a Founder member of Pratiti Technologies, he is committed to applying his management learning as well as the passion for building new solutions to realize your innovation with certainty.

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