Every NICU medical staff member is battle-hardened and possesses a pair of discerning eyes. However, when a flood of vital data pours in, even the most discerning eyes can be easily confused by the complexities. We can't help but wonder: Is that steady curve hiding the prelude to a storm? Amidst massive, heterogeneous, and fragmented data, how can we hear the faintest whispers of help? Has the clinical diagnosis and treatment truly achieved the expected results?

We understand that clinical experience is irreplaceable, but we firmly believe that technology can complement this experienced eye with an AI-powered perspective. Likang Group is committed to developing a critical care patient vital signs monitoring and decision support system (NICU CDSS), bringing an "AI eye" to NICU clinical practice. It doesn't replace judgment; it empowers insight, helping medical staff penetrate the data fog and transition from passive monitoring to intelligent prediction, accelerating 

Seeing the Big Picture

From Data Silos to Multimodal Fusion

The truth begins with a complete data landscape. The primary capability of these "AI eyes" is to break down data silos! They employ a multi-layered data fusion strategy, integrating not only basic vital signs like heart rate and blood oxygen levels, but also seamlessly integrating multimodal information such as ventilator mechanical data, laboratory test results, nutritional management data, and even clinical notes from EMRs. By adhering to relevant standards, they can rapidly transform a seemingly unrelated collection of numbers into a logically structured, multidimensional snapshot of a patient's status, providing a basis for subsequent diagnosis, treatment, and outcome evaluation.

Millisecond Insights

Digital Twins Built with AI and Edge Computing

In the ever-changing NICU environment, millisecond-level changes hold crucial implications. Studies have shown that subtle variations in heart rate can signal sepsis a full 12 hours in advance; dramatic fluctuations in blood oxygen levels are directly linked to brain damage and retinopathy; and subtle deviations in nutrition and fluid management can determine whether a child survives extrauterine growth restriction.

By letting the data speak for itself, we can shift the clinical focus from "post-event rescue" to "pre-event intervention." The core of the "AI Eye" system is to build a real-time "digital twin" model for each patient, instantly digesting all bedside data and uncovering deep connections imperceptible to the naked eye. This "translates" invisible risks into accurate warning signals, enabling medical staff to identify and intervene early.

From data chain to decision chain

CI+ML dual engine drive

As one leading expert put it, "Digital twins don't replace doctors; rather, they become their 'super brain'—making hidden risks visible and transforming empirical decision-making into data-driven."

The ultimate mission of these "AI eyes" is to leverage the powerful dual engines of computational intelligence (CI) and machine learning (ML) to provide powerful support from the "data chain" to the "decision chain." Through interconnected core capabilities, they seamlessly integrate predictive insights into clinical workflows.

Real-time Twin

The system builds a digital model for each patient, updating it in real time at a frequency of seconds, visualizing their complete physiological state. This not only aggregates data but also transforms fragmented information into an intuitive, dynamic, and interactive life-image, providing a holistic perspective for subsequent decision-making.

Decision Support

At each critical decision point, such as adjusting oxygen therapy and initiating antibiotics, the system proactively delivers evidence-based treatment recommendations. This is achieved thanks to the deep learning (DL) model's accurate prediction of risks like sepsis and the reinforcement learning (RL) model's ability to dynamically optimize ventilator parameters. More importantly, the system utilizes Explainable AI (XAI) technology to clearly present the basis for its decisions, enabling doctors to understand not only the results but also the reasons behind them, thereby building true trust between the patient and the machine.

Quality Loop

These "AI eyes" not only focus on the present but also look to the future. It can establish a closed-loop quality system through retrospective analysis of adverse events, continuously iterating and optimizing clinical pathways, ensuring that each diagnosis and treatment becomes the cornerstone for better decisions for the next.

In life's first battleground, our NICU "AI Eye" is becoming the "fourth dimension of power" protecting life. It frees doctors from data silos, allowing them to focus on decision-making and care. This represents a profound shift from "passive response" to "proactive foresight."

HealForce Group's mission is to build AI-powered digital system solutions, from data collection and intelligent analysis to aided diagnosis and treatment decision-making. We are establishing a new patient-centric, data-driven, human-machine collaborative digital twin intelligent NICU ecosystem, setting a new benchmark for pediatric medicine. Our future is one where every child has their own "digital guardian"!