These new medical procedure software applications and ABIS database technologies organize, train and learn from medical surgery processes. The medical artificial intelligence algorithms learn in 3 ways:
By visually capturing all physical movement procedures by all medical staff as well as machines and converting them into algorithms for the ABIS database;
By having medical staff (not at the same time) verbally speak all (beginning to conclusion) procedures into a medical procedure chatbot that converts them into algorithms and organized in the ABIS database;
And finally having the machines (robots and sometimes drones), the medical staff (humans), and the intersection of both physical, verbal, as well all other types of hard data converted into algorithms for the ABIS database in real time.
Patents are pending worldwide.
June 22, 2025 InTeleCal LLC. Medical Robotic self directed autonomous physical procedure application 128 filed. The new disclosure can operate in surgical procedures without any medical staff intervention or monitoring. Mechanical arms, hands and fingers, tracking devices affixed to fingertips, primary/secondary robotic manual patient tissue/bodily fluids evaluation in real time, quantum computing, mimic software, lidar/lasers/headsets/chatbots/simulation software/green screen application, ambient listening technology and digital scent technology all incorporated in new disclosure.
June 12, 2025 Numerous USPTO patent applications have been filed for “Self Directed AI Autonomous Medical Procedures”. The “MedsApp.ai” AI applications are both a training method and medical autonomous application without any medical staff intervention and or monitoring. InTelecal LLC is seeking professionals to help training and funding. “contact@intelecal.ai"
All data including but not limited to temperatures, humidity, atmospheric dust and debris, levels of lighting, ratios of biosurfactants utilized, how many staff and machines (stationary and roaming) were involved in the procedures (hard data), how many robotic arms were required, and finally was the procedure successful (future data) and why not whereby all data (imaging, verbal and hard data) is converted into algorithms for the ABIS (Automated Biosensing Imaging System) database “biosensing.ai”.
Another component of the ABIS algorithms is the detection (utilizing the UMMDA) and elimination pathogens and disease spreading matter (utilizing biosurfactants) that may affect patients as well as medical staff.
There are 5 types of algorithms in the ABIS database, successful procedures, unsuccessful procedures, management of all facets of the ABIS database applications, forecasting algorithms of possible future events in the medical operating rooms, and error algorithms.
Robots and Drones scan for disease causing micro organisms before, during and after medical surgical procedures utilizing biosurfactants to mitigate disease spread.
UMMDA - Universal Multipurpose Matter Detection Application using AI
“UMMDA” USPTO and WIPO Patents pending worldwide. The UMMDA is an Artificial Intelligence and Machine Learning Apparatus that detects all types of Bacteria, Viruses, Fungus, Allergens and Micro Organisms (all types of Medical matter) abnormal cells, bodily fluids, and abnormal blood cells with accuracy that can be dialed up or down in real time. See Database example webpage de3.ai/database to see a general understanding of how ABIS database works.