US 2026/0066085 A1 · System and Method for AI-Driven Surgical Care Recommendation and Optimization

Abstract

A system and method for recommending surgical care providers and protocols using artificial intelligence (AI) and machine learning (ML) is disclosed. The system comprises one or more processors coupled to a memory that stores instructions for receiving healthcare data from various sources, preprocessing the data, training an ML model to generate recommendations, and iteratively refining the model based on patient feedback. The system receives data related to surgical procedures, hospitals, doctors, and pre- and post-operative care, preprocesses the data using techniques such as data cleaning, normalization, and encoding, and trains a neural network model to generate recommendations for selecting optimal hospitals, doctors, and care protocols. The generated recommendations are provided to users via an intuitive interface, and patient feedback is used to retrain and optimize the ML model for continuous improvement.

Claims20

Dependent claims

A system for recommending surgical care providers and protocols, comprising:

a. one or more processors coupled to a memory, the memory storing instructions that, when executed by the one or more processors, cause the system to:
i. receive healthcare data from a plurality of sources, the healthcare data related to surgical procedures, hospitals, doctors, and pre and postoperative protocols;
ii. preprocess the received healthcare data to ensure data quality;
iii. train a neural network model using the preprocessed healthcare data to generate recommendations for selecting hospitals and doctors for particular surgical procedures;
iv. train the neural network model using the preprocessed healthcare data to generate recommendations for preoperative and postoperative protocols for particular surgical procedures;
v. provide the generated recommendations to a user via a user interface;
vi. receive feedback data from patients related to the recommendations;
and
vii. retrain the neural network model based on the received feedback data to iteratively refine the recommendations.

6 more elements

A method for generating surgical care recommendations using artificial intelligence, comprising:

a. receiving, by one or more processors coupled to a memory, healthcare data from a plurality of sources, the healthcare data related to surgical procedures, hospitals, doctors, and pre and postoperative care;
b. preprocessing, by the one or more processors, the received healthcare data to ensure data quality;
c. training, by the one or more processors, a machine learning model using the preprocessed healthcare data to:
d. rank hospitals and doctors based on their suitability for particular surgical procedures, and
e. determine optimal medication regimens and care protocols for preoperative and postoperative periods for particular surgical procedures;
f. outputting, by the one or more processors, the rankings and determinations as recommendations to a user;
g. receiving, by the one or more processors, feedback data from patients related to the recommendations;
and
h. retraining, by the one or more processors, the machine learning model based on the received feedback data to optimize the recommendations.

6 more elements

Dependencies are inferred from the claim text.

System and Method for AI-Driven Surgical Care Recommendation and Optimization

Life of this patent

System and Method for AI-Driven Surgical Care Recommendation and Optimization

Life of this patent

Abstract

Claims20