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Delivering value and transforming performance in healthcare through AI

 

Driving cost out of medical process

  • Surgical equipment - instrument tray imaging
  • Digital pathology - microscopic tissue feature detection
  • Telemedicine - remote life signs measurement
  • Digital stethoscope - heart murmur detection

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5 major causes of failure in medical AI projects and how to overcome them

Medical AI is a powerful tool that can do a lot of good. It’s also glamorous: leads to much innovation and attracts a lot of mainstream media.

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Here are some examples of our recent work

Deep Learning in detection of microscopic tissue features
Deep Learning in detection of microscopic tissue features 1
Deep Learning in detection of microscopic tissue features 2

Deep Learning in detection of microscopic tissue features

 

Digica was tasked with detecting features in digitised microscopic tissue images. The project was unorthodox due to the scarcity of labelled examples and the target images having resolution in the order of thousands of megapixels.

The project demanded segmentation or detection of features such as cell nuclei, artefacts and microvessels.

Preventing cot deaths using radar

 

We used a small radar system to monitor a baby's breathing pattern.

For every 2000 babies born, one of them will stop breathing in the middle of the night and die. We want to prevent this by creating an automatic, remote breath control device that triggers an alarm when the baby has difficulty breathing.

Preventing cot deaths using radar
Preventing cot deaths using radar 1
Preventing cot deaths using radar 2
Measuring various life signs using smartphone derived facial video
Measuring various life signs using smartphone derived facial video 1
Measuring various life signs using smartphone derived facial video 2

Measuring various life signs using smartphone-derived facial video

 

We created a cross platform library for in-vehicle and remote diagnostic human monitoring.

Using photoplethysmography (PPG) and a standard RGB camera, blood volume changes were detected to measure heart rate variability, respiration rate and blood oxygen saturation.

Optimisation of surgical instrumentation usage

 

Driven by computer vision and synthetic data, a deep learning model is incorporated into a mobile application allowing medical personnel to automatically identify medical trays and their contents for use in surgery.

Before surgery, staff take a picture of a surgical tool tray using their smartphone and are notified if instruments are missing.

After surgery, staff are able to determine which instruments have been used or may be missing.

Optimisation of surgical instrumentation usage
Optimisation of surgical instrumentation usage 1
Optimisation of surgical instrumentation usage 2
AI Edge supports people with impaired vision 01
AI Edge supports people with impaired vision 02
AI Edge supports people with impaired vision 03

AI Edge supports people with impaired vision

 

Supporting people with impaired vision by detecting nearby obstructions has been achieved by applying computer vision through a camera integrated into a walking stick.

Our AI-based object detection system recognises surfaces and moving objects based on proximity and potential hazard and communicates this via a haptic controller and Bluetooth earpiece.

The first prototype implementation is being trialled with Blackworld, a blind and partially sighted organisation in Poland

FAQ

Frequently Asked Questions

All FAQ
What are the key benefits of using AI for clinical documentation in healthcare?
  • Improved Accuracy: AI reduces human errors in medical documentation, ensuring precise and standardized records.
  • Time Efficiency: Automating documentation tasks allows healthcare professionals to focus more on patient care.
  • Better Compliance: AI ensures adherence to medical coding standards and regulatory requirements.
  • Enhanced Data Insights: AI extracts valuable insights from clinical notes, helping with better decision-making.
  • Cost Reduction: By optimizing workflows and reducing administrative overhead, AI lowers operational costs.
How does AI assist in predictive health analytics?

Predictive health analytics powered by AI can identify patients at risk of developing certain conditions before symptoms appear. AI models analyze historical health data, lifestyle patterns, and genetic factors to forecast potential health risks. This allows doctors to intervene early, personalize treatments, and improve preventive care strategies. AI has been applied to areas like heart rate variability analysis, respiratory rate monitoring, and early detection of diseases through medical imaging.

What AI tools are available for healthcare billing and payment systems?

AI-powered solutions in billing and payment systems enhance accuracy, detect fraud, and optimize revenue cycle management. AI-driven automation helps process claims efficiently, reducing human errors and ensuring timely reimbursements. Machine learning models can analyze billing patterns, detect anomalies that indicate fraudulent activities, and streamline payment workflows, improving financial management for healthcare providers.

What AI solutions are used in clinical documentation?

AI in clinical documentation helps automate and streamline medical record-keeping, reducing the administrative burden on healthcare professionals. Technologies like Natural Language Processing (NLP) extract key insights from medical notes, improve documentation accuracy, and ensure compliance with medical standards. AI can also assist in summarizing patient histories, identifying missing information, and improving coding for billing and compliance purposes.

How does AI improve healthcare outcomes?

AI enhances healthcare outcomes by enabling faster, more accurate diagnoses, improving treatment planning, and assisting in patient monitoring. Machine learning models can detect diseases earlier, such as lung conditions in X-rays, classify body parts in medical imaging, and even analyze tissue samples to identify anomalies. AI-driven solutions also support predictive health analytics, allowing healthcare providers to anticipate and prevent potential complications, ultimately leading to better patient care and reduced hospitalizations.

How can I collaborate with Digica on AI healthcare projects?

We offer a free consultation to discuss your AI needs. Get started in 3 steps:

  1. Schedule a Consultation – Talk with our AI experts about your healthcare challenges
  2. Receive a Custom AI Strategy – Get a tailored AI roadmap for measurable results
  3. Implement & Scale – Integrate the AI solution and track its impact on performance

 Contact us today to explore AI-powered healthcare innovations with Digica!

Can Digica customize AI solutions for my healthcare organization?

Yes! We develop custom AI solutions tailored to your hospital, clinic, or healthcare system. Whether you need:

  • AI-powered diagnostics
  • Predictive analytics
  • Medical imaging automation
  • Hospital workflow optimization
  • Information extraction from medical reports (radiology and pathology)

Digica’s AI team can design, train, and deploy a solution that meets your specific needs.

How does Digica ensure data security in AI-powered healthcare solutions?

We follow strict data security and compliance protocols, including:

  • GDPR & HIPAA compliance
  • Federated Learning (privacy-preserving AI)
  • Data encryption & secure model training
  • Ethical AI frameworks to protect patient confidentiality
How does Digica’s AI track human features for remote medical diagnosis?

Digica has developed an AI-powered human feature tracking platform that monitors physical and mental health indicators using a standard RGB camera. This system can:

  • Measure heart rate through facial analysis
  • Track head and hand movements for early signs of cognitive or physical decline
  • Analyze gaze direction and micro-expressions to assess emotional state
  • Monitor seniors at home remotely, supporting early intervention and diagnosis

Results:
✔ Tracks six different human health indicators
✔ Designed for future expansion (e.g., blink detection, audio transcription, speech analysis)
✔ Enables remote patient monitoring, enhancing healthcare accessibility

How does AI help hospitals with inventory and surgical tool management?

Digica’s AI-powered computer vision technology automatically tracks and recognizes hospital surgical tools. This helps:

  • Reduce errors in surgical procedures
  • Prevent the loss of expensive medical instruments
  • Streamline hospital inventory management

"There aren’t that many people who have as good a knowledge base as the Digica team."

 

Leading global imaging technology company

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Digica’s cooperation model is flexible, so that we can match our services to your goals, resources and timeline. Consistency and transparency are key to our delivery process, so we follow the same framework regardless of the project.
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