Neurokit Healthcare 1-4

https://ko-fi.com/psinergy
Come join us for many stem cells and groovey tunes!
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https://x.com/dr_edwardgroup/status/1907869168696750194

https://neuropsychology.github.io/NeuroKit/introduction.html

https://link.springer.com/article/10.3758/s13428-020-01516-y

Neurophysiological signal processing involves using algorithms to analyze and enhance brain activity signals (like EEG and fMRI) recorded from the nervous system, ultimately aiding in understanding brain mechanisms and identifying patterns related to various states and conditions.

https://neuropsychology.github.io/NeuroKit/

open source python toolbox

In the context of Body Area Networks (BANs), Python is used for developing and managing software applications, simulating network behavior, and potentially implementing telecare systems, leveraging its flexibility and ease of use

https://www.mdpi.com/1424-8220/21/16/5504

https://dl.acm.org/doi/abs/10.1145/3345768.3355939

https://dl.acm.org/doi/proceedings/10.1145/3345768

https://mswimconf.com/2025/

ISO/IEEE 11073 standard

https://en.wikipedia.org/wiki/ISO/IEEE_11073_Personal_Health_Data_Standards

https://www.iso.org/committee/6266604.html

https://www.iso.org/committee/54960.html

https://www.iso.org/about

https://www.sciencedirect.com/science/article/abs/pii/S1383762122000662#:~:text=BANSIM%20is%20a%20DRL%2Denabled,with%20a%20DRL%20development%20environment

DRL-enabled discrete-event network simulator

Deep Reinforcement Learning (DRL) algorithms combine reinforcement learning with deep neural networks to enable agents to learn complex tasks from raw input data, such as pixels, without manual feature engineering. Key algorithms include Deep Q-Networks (DQN), Policy Gradient Methods, and Actor-Critic methods.

A Deep Q-Network (DQN) is a reinforcement learning algorithm that uses deep neural networks to approximate the Q-value function, enabling agents to learn optimal policies in complex environments where traditional Q-learning with tables becomes impractical.

In the context of reinforcement learning, a Q-value function, or action-value function, estimates the expected cumulative reward for taking a specific action in a given state and then following a particular policy.

https://www.researchgate.net/publication/359688563_BANSIM_A_new_discrete-event_simulator_for_wireless_body_area_networks_with_deep_reinforcement_learning_in_Python#:~:text=Request%20PDF%20%7C%20BANSIM:%20A%20new%20discrete%2Devent,body%20area%20networks%20(WBANs).%20However%2C%20it%20was

https://rumble.com/user/Psinergy?q=biopython

eHealth" refers to the use of digital technologies, like computers and the internet, to deliver and manage healthcare information and services, encompassing areas like electronic health records, telemedicine, and online health education.

https://fhir.org/

https://en.wikipedia.org/wiki/Fast_Healthcare_Interoperability_Resources

HL7 is a set of international standards for the exchange of electronic health information (EHI) between healthcare software applications. It provides a common language and framework for ensuring interoperability and data consistency in the healthcare industry.

https://onlinelibrary.wiley.com/doi/epdf/10.1002/wcm.884

internet of behaviors

The Electronic Integrated Disease Surveillance System (EIDSS) is a software system designed to strengthen monitoring and prevention of human and animal diseases within the "One Health" concept, facilitating compliance with the International Health Regulations (IHR) 2005.

https://www.iec.ch/system/files/2023-10/wsdcombinedpdf_0.pdf

https://iec.ch/standards-development

Point-of-care (PoC) medical device communication, governed by standards like ISO/IEEE 11073, enables seamless data exchange between devices and healthcare systems, facilitating better patient care and improved workflows.

https://x.com/ET_sharing/status/1908605797384282542

https://pmc.ncbi.nlm.nih.gov/articles/PMC7909758/

COV WBAN

https://www.techscience.com/cmc/v70n2/44669/html

https://www.mdpi.com/2224-2708/12/2/20

https://www.mdpi.com/1424-8220/23/4/2042

https://www.sciencedirect.com/science/article/pii/S1532046421000605

human activity recognition radar
Mark 5:36
amen