Update README.md

README.md

@@ -8,24 +8,22 @@ tags:
 ---
 
 ## Important Notice
-This model is provided for evaluation and development purposes
-only. It is not validated for and must not be used in clinical,
-diagnostic, or production settings. See #use-and-limitations.
+This model is provided for evaluation and development purposes only. It is not validated for and must not be used in clinical, diagnostic, or production settings. See #use-and-limitations and #License.
 
 ---
 ## Model Information
 
 ### Description
 patient-present is a single-stage object detection model that localizes
-a neonate/infant patient inside a NICU radiant warmer from a video frame.
+a figure within a boxed physical space from a video frame.
 It uses a MobileNetV2 backbone with a Feature Pyramid Network (FPN) neck
 and an anchor-free single-stage detection head, following the
 mmdetection framework conventions. This model is a development and evaluation
 tool produced as part of Intel's NICU Warmer reference design and has not
-undergone clinical validation.
+undergone clinical validation. In this reference application, the detection of the figure in the boxed space in the video frame is designed to mimic the workload of an AI model in a real neonatal scenario where the model would detect the presence of an infant/ neonatal patient in the NICU Warmer. 
 
 ### Intended Use
-This model is intended for use by software developers and researchers evaluating AI-assisted monitoring workflows on Intel hardware. It is designed to demonstrate detection feasibility in a NICU warmer context. patient_present itself does not provide any medical functionality, nor is it intended to process or interpret medical data for a medical purpose. Developers are responsible for independently validating and adapting patient-present for their specific use case. It must not be used in live clinical environments, for diagnostic decisions, or on live patients.
+This model is intended for use by software developers and researchers evaluating AI-assisted monitoring workflows on Intel hardware. It is designed to demonstrate detection feasibility within a non-clinical artificial context. patient-present itself does not provide any medical functionality, nor is it intended to process or interpret medical data for a medical purpose. Developers are responsible for independently validating and adapting patient-present for their specific use case. It must not be used in live clinical environments, for diagnostic decisions, or on live patients.
 
 ---
 ## Technical Specifications
@@ -39,6 +37,14 @@ This model is intended for use by software developers and researchers evaluating
 | Training hardware | Intel Ultra Core      |
 | Framework         | PyTorch (mmdetection) → OpenVINO IR FP32         |
 
+---
+## Training Data
+The model was trained using images of a box-like compartment taken from above. These images were created by the development team for this purpose.
+Within the box compartment (representing the NICU Warmer), numerous images show different configurations of scenarios i.e. the presence or absence of a plastic figure (representing the “patient”), the presence or absence of a hand (representing the “caretaker”) and the presence or absence of latch clips (representing the NICU Warmer hood latch). 
+The model is trained to recognise the presence of a plastic figure within this environment. Once trained, you can test the performance of the AI model and by extension the hardware in real-time to mimic production use. Whilst the training process allows for simulation of production workloads, the fact that the training data has no clinical nexus demonstrates that the NICU Warmer reference application was not intended for use within a production, clinical environment. 
+## Evaluation
+Evaluation was limited to confirmation that the model can recognise the presence of a plastic figure in the environment described above. No formal evaluation of performance was undertaken. It is recognised that reference AI workloads may not replicate real, production workloads
+
 ---
 ## Use and Limitations
 
@@ -46,17 +52,13 @@ This model is intended for use by software developers and researchers evaluating
 - Evaluation and benchmarking of Healthcare and Life Sciences AI workflows
 - Research and development
 - Academic study
-- Adaptation and modification for non-clinical applications
-
 ### Prohibited Uses
 - Clinical or diagnostic use
-- Production deployment without independent validation and
-  applicable regulatory authorization
-- Use with live patients or real patient data (unless the user
-  has obtained all necessary authorizations)
-- Any use that would cause Intel to be treated as the
-  manufacturer, provider, or deployer of a medical device
-  or regulated AI system
+- Production deployment
+- Use with live patients or real patient data
+### Known Limitations
+- No evaluation of performance undertaken
+- No evaluation of whether reference AI workloads will replicate real, production workloads
 
 ---
 ## License