AI Solutions for Healthcare: Development Services

AI is set to shape the future of healthcare industry, addressing critical challenges while enhancing patient outcomes, driving operational efficiency, and reducing costs.

Unicsoft’s ISO certified team is well-equipped to build risk-free healthcare AI solutions compliant with HIPAA & EU AI Act regulations.

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Next-Gen Healthcare Solutions Powered by AI

Early symptom prediction

Early symptom prediction

AI and ML analyze patient data, enabling early disease detection, precise diagnoses, operational efficiency for healthcare institutions, improved patient outcomes, and cost reduction for health insurance.
Cancer prognostic model

Cancer prognostic model

A predictive cancer prognosis model that integrates histology and genomic data through AI and deep learning, resulting in more precise treatments, improved patient outcomes, and valuable insights for cancer research.
Hospital stay forecast

Hospital stay forecast

The use of AI tools in predicting long-term hospital stays helps optimize resource management and personalized care, offering strategic benefits to healthcare professionals and improved health outcomes for patients.
Personalized medications and care

Personalized medications and care

The AI system, by leveraging machine learning and comprehensive patient data, facilitates personalized treatment plans in healthcare, enhancing treatment effectiveness, improving patient health outcomes, and leading to cost savings in the healthcare sector.
Real-time prioritization and triage

Real-time prioritization and triage

AI-based patient triaging systems, employing techniques like natural language processing, machine learning, and computer vision, offer a streamlined solution to prioritize and match patients to the appropriate healthcare provider, enhancing efficiency, and patient outcomes.
Deep research into neurological disorders

Deep research into neurological disorders

AI-based patient triaging systems, employing techniques like natural language processing, machine learning, and computer vision, offer a streamlined solution to prioritize and match patients to the appropriate healthcare provider, enhancing efficiency, and patient outcomes.
Healthcare management through intelligent automation

Healthcare management through intelligent automation

An AI-powered automation engine can streamline data management in healthcare by integrating various data sources, capturing relevant clinical data, and using ML to identify critical information, leading to improved efficiency and more informed decision-making.
Virtual assistants in healthcare

Virtual assistants in healthcare

Leveraging artificial intelligence (AI) and natural language processing (NLP), chatbots can perform various tasks efficiently and accurately: appointment scheduling, patient triage, basic inquiries, symptom checker, medical research assistance.

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Planning to develop a healthcare AI solution with minimized risks?

Challenges of Healthcare AI Solution Development

Mastering AI in healthcare demands tackling intricate challenges, from technical complexities to ethical and regulatory considerations.
Data Drought

Quality data fuels reliable insights from healthcare AI. Preparing clear, complete, and accurate datasets is pivotal for successful medical AI projects.

Regulation Compliance

In a regulated healthcare landscape, meeting HIPAA, FDA, or GDPR requirements is paramount. Our expertise ensures functional and compliant AI healthcare solutions, mitigating privacy risks.

Black-box Issue

In healthcare, transparent AI is essential. Our developers strike the ideal balance between model complexity, accuracy, and explainability, ensuring doctors grasp AI-generated recommendations.

Data Security

Healthcare AI demands substantial data for precision, but data security is crucial. We fortify against breaches with robust measures like advanced threat detection, activity control, and anonymization.

Infrastructure Scalability

AI model training and testing demand scalable, reliable infrastructure. Navigating cloud provider choices is vital. We guide your AI healthcare project, ensuring the right infrastructure fit for evolving data volumes.

Seamless Integration

Real value in healthcare AI demands seamless integration with existing systems, but complex software can trigger compatibility issues. Our team readies your IT infrastructure for AI implementation, ensuring system harmony.

Unicsoft's Approach to Navigating AI Challenges in Healthcare

HIPPA compliant
We set a unique approach field-tested by Unicsoft to develop truly HIPAA compliant healthcare systems.
Undisputed quality
Unicsoft is ISO 25010 certified, ensuring our quality control spans functional suitability, reliability, performance, security, and more across all our projects.
Stress-free compliance
The datasets and AI technologies are secure and compliant with GDPR and EU AI Act recommendations.
High speed, low cost
The Lean methodology and low-code tools allow us to deliver a testable prototype without breaking the bank within weeks, not months.
Looking for a top-rated development team to build or enhance your own healthcare AI solution?

Facts in Figures

15+
Countries Covered
200+
Delivered Projects
93%
Customer Retention Rate
4 Years
Our Average Partnership Duration
75%
of Сlients note our Project Management Excellence
200 000+
Talent Pool

Our Process of Medical AI Software Development

01
Requirement analysis
First, we define the challenges you want to solve with a healthcare AI solution. Our team identifies your goals, requirements, and preferences. We also outline the scope of the project and prepare paperwork.
02
Data exploration
At this step, we explore the data to uncover its characteristics, structure, and patterns. Data exploration is essential for gaining greater insights into what we will work with and for further data analysis.
03
Building a model
Now, we are ready to create, train and evaluate an AI model for your project. An AI model will need enough data to meet your requirements. So, at this step, we may also go back to the data collection, structuring, and labeling process.
04
AI solution development
At this stage, we engineer the features of your AI healthcare solution. Basically, that’s the phase when your idea finally turns into a real product.
05
QA & testing
The testing phase is essential to ensure your healthcare AI solution is bug-free and functions as intended. It involves creating test cases, writing scripts, and executing them to spot any issues.
06
Support
The support stage involves performance monitoring, updates, and troubleshooting. You may also need your model re-trained to comply with the changing goals.
01. Requirement analysis
First, we define the challenges you want to solve with a healthcare AI solution. Our team identifies your goals, requirements, and preferences. We also outline the scope of the project and prepare paperwork.
02. Data exploration
At this step, we explore the data to uncover its characteristics, structure, and patterns. Data exploration is essential for gaining greater insights into what we will work with and for further data analysis.
03. Building a model
Now, we are ready to create, train and evaluate an AI model for your project. An AI model will need enough data to meet your requirements. So, at this step, we may also go back to the data collection, structuring, and labeling process.
04. AI solution development
At this stage, we engineer the features of your AI healthcare solution. Basically, that’s the phase when your idea finally turns into a real product.
05. QA & testing
The testing phase is essential to ensure your healthcare AI solution is bug-free and functions as intended. It involves creating test cases, writing scripts, and executing them to spot any issues.
06. Support
The support stage involves performance monitoring, updates, and troubleshooting. You may also need your model re-trained to comply with the changing goals.

What our clients say

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What our clients say

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    Frederik Bonde
    Unicsoft partner, founder @paterhn.ai
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    Regional Director
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    FAQ

    How is AI used in healthcare?plus
    AI can cause an actual revolution in healthcare. It is already being used worldwide for diagnostics and treatment support, clinical decision-making, and real-time remote patient monitoring. Other important applications of AI solutions in healthcare are medicine development and clinical studies.
    Why does your healthcare organization need to adopt AI?plus
    AI solutions in healthcare help improve patient outcomes and experience, streamline hospital workflow, reduce medical costs, and make clinical services more effective in general. By using AI-enabled tools, clinicians can better understand the patient’s medical history and current conditions, identify potential risks, and start treatment early on.
    What AI technologies can be used in healthcare?plus
    Artificial intelligent technologies that can be used for building an AI healthcare solution include machine learning, deep learning, natural language processing, and computer vision.
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