PREDICTION AND DETECTION OF LIVER CIRRHOSIS DISEASE THROUGH AI FROM SECURED BLOCK CHAIN BASED LIVER CIRRHOSIS DATASET

Abstract

ABSTRACT “PREDICTION AND DETECTION OF LIVER CIRRHOSIS DISEASE THROUGH AI FROM SECURED BLOCK CHAIN BASED LIVER CIRRHOSIS DATASET” The present invention provides Prediction and detection of liver cirrhosis disease through AI from secured block chain based liver cirrhosis dataset. In the healthcare sector of India, significant challenges persist, particularly concerning medical accessibility and language barriers. A substantial portion of India's population faces obstacles due to limited proficiency in English, hindering their ability to read or write in the language. Nowadays Liver Cirrhosis (LC) is a common disease in India like Country. The common causes of Liver Cirrhosis are Alcohol Consumption, Hepatitis B and Hepatitis C. Patients have to store their data in the block chain database. This cloud-based system with block chain has good data security and the Artificial Intelligence (AI) technology has the feature to analyses patient's medical reports and make prescriptions in patient's understandable language. Figure 1

Specification

Description:TECHNICAL FIELD
[0001] The present invention relates to the field of medical science, and more particularly, the present invention relates to the prediction and detection of liver cirrhosis disease through AI from secured block chain based liver cirrhosis dataset.
BACKGROUND ART
[0002] The following discussion of the background of the invention is intended to facilitate an understanding of the present invention. However, it should be appreciated that the discussion is not an acknowledgment or admission that any of the material referred to was published, known, or part of the common general knowledge in any jurisdiction as of the application's priority date. The details provided herein the background if belongs to any publication is taken only as a reference for describing the problems, in general terminologies or principles or both of science and technology in the associated prior art.
[0003] Nowadays Liver Cirrhosis is the most common disease country like India, Medical Testing accessibility and Language barriers are the key problems. So accessing patient data to doctors and the prescriptions prescribed by doctors available to patients in their Native Language are challenging tasks.
[0004] In light of the foregoing, there is a need for Prediction and detection of liver cirrhosis disease through AI from secured block chain based liver cirrhosis dataset that overcomes problems prevalent in the prior art associated with the traditionally available method or system, of the above-mentioned inventions that can be used with the presented disclosed technique with or without modification.
[0005] All publications herein are incorporated by reference to the same extent as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference. Where a definition or use of a term in an incorporated reference is inconsistent or contrary to the definition of that term provided herein, the definition of that term provided herein applies, and the definition of that term in the reference does not apply.
OBJECTS OF THE INVENTION
[0006] The principal object of the present invention is to overcome the disadvantages of the prior art by providing Prediction and detection of liver cirrhosis disease through AI from secured block chain based liver cirrhosis dataset.
[0007] Another object of the present invention is to provide Prediction and detection of liver cirrhosis disease through AI from secured block chain based liver cirrhosis dataset that are small in size and have the feature of data transformation.
[0008] Another object of the present invention is to provide Prediction and detection of liver cirrhosis disease through AI from secured block chain based liver cirrhosis dataset that requires distributed operational cost management.
[0009] Another object of the present invention is to provide Prediction and detection of liver cirrhosis disease through AI from secured block chain based liver cirrhosis dataset that is flexible to adoption.
[0010] Another object of the present invention is to provide Prediction and detection of liver cirrhosis disease through AI from secured block chain based liver cirrhosis dataset that has interoperability.
[0011] Another object of the present invention is to provide Prediction and detection of liver cirrhosis disease through AI from secured block chain based liver cirrhosis dataset that is Patient and Environmental friendly.
[0012] The foregoing and other objects of the present invention will become readily apparent upon further review of the following detailed description of the embodiments as illustrated in the accompanying drawings.
SUMMARY OF THE INVENTION
[0013] The present invention relates to Prediction and detection of liver cirrhosis disease through AI from secured block chain based liver cirrhosis dataset.
[0014] Patient data are maintained in a decentralized cloud-based blockchain database system. Every patient has their patient ID and Aadhar card Number so that Doctors can identify patients uniquely. All the patient's general data and medical test data are stored and updated in the block of block chain. Which can be available for all doctors worldwide with block chain security? So patients can also reach good doctors worldwide.
[0015] Some hilly and forest areas do have not good communication systems. In that case, we have small devices like the Mini Ultrasound Machine and Mini CBC test Machine which can be easy to relocate from one place to another place. These devices communicate with clouds through the internet so that unique patient medical test reports can be uploaded to the chain database.
[0016] If any patients have already done their medical tests can scan their medical reports by Nano-Net OCR Engine and upload them to the cloud. Text-based report data are trained by a Gated Recurrent Unit (GRU) to classify the Liver affected by Cirrhosis or Healthy then sent to the block of blockchain database. At the same time if the patient needs an ultrasound, then the ultrasound image data are uploaded to the cloud, classified by ResNet-50 and send results to the blockchain database as shown in Figure 1. When a Patient needs any doctor consultancy doctor can fetch data from the block of data block-chain. If the patient is in a remote area and can connect with the doctor, then an Encoder-Decoder and Attention Mechanism based Open-NMT system which is an Open Source translator helps to translate patients to understand doctor's prescription in their native language as shown in Figure 2.
[0017] For Optical Character Recognition (OCR), leveraging robust engines like Tesseract-OCR can be used. Instead of using a GRU classifier, more effective choices include LSTM and CNN-based classifiers, especially for text report analysis. When analysing of ultrasound image data, CNN and advanced architectures like ResNet models are suitable. For translation tasks, opting for the Hugging Face transformer system can be used.
[0018] Novel aspects of the invention: As data are storing in Decentralized in the block chain the security aspect of data will more effective and the Liver Cirrhosis patients can check their health in their home or nearer medical test center also patient can connect with doctors with worldwide with zero misguidance.
[0019] While the invention has been described and shown with reference to the preferred embodiment, it will be apparent that variations might be possible that would fall within the scope of the present invention.
BRIEF DESCRIPTION OF DRAWINGS
[0020] So that the manner in which the above-recited features of the present invention can be understood in detail, a more particular description of the invention, briefly summarized above, may have been referred by embodiments, some of which are illustrated in the appended drawings. It is to be noted, however, that the appended drawings illustrate only typical embodiments of this invention and are therefore not to be considered limiting of its scope, for the invention may admit to other equally effective embodiments.
[0021] These and other features, benefits, and advantages of the present invention will become apparent by reference to the following text figure, with like reference numbers referring to like structures across the views, wherein:
[0022] Figure 1. Process diagram of uploading and accessing of data label of patients and doctors.
[0023] Figure 2. Liver Cirrhosis patient's report analysis and prescription translation.
DETAILED DESCRIPTION OF THE INVENTION
[0024] While the present invention is described herein by way of example using embodiments and illustrative drawings, those skilled in the art will recognize that the invention is not limited to the embodiments of drawing or drawings described and are not intended to represent the scale of the various components. Further, some components that may form a part of the invention may not be illustrated in certain figures, for ease of illustration, and such omissions do not limit the embodiments outlined in any way. It should be understood that the drawings and the detailed description thereto are not intended to limit the invention to the particular form disclosed, but on the contrary, the invention is to cover all modifications, equivalents, and alternatives falling within the scope of the present invention as defined by the appended claim.
[0025] As used throughout this description, the word "may" is used in a permissive sense (i.e. meaning having the potential to), rather than the mandatory sense, (i.e. meaning must). Further, the words "a" or "an" mean "at least one" and the word "plurality" means "one or more" unless otherwise mentioned. Furthermore, the terminology and phraseology used herein are solely used for descriptive purposes and should not be construed as limiting in scope. Language such as "including," "comprising," "having," "containing," or "involving," and variations thereof, is intended to be broad and encompass the subject matter listed thereafter, equivalents, and additional subject matter not recited, and is not intended to exclude other additives, components, integers, or steps. Likewise, the term "comprising" is considered synonymous with the terms "including" or "containing" for applicable legal purposes. Any discussion of documents, acts, materials, devices, articles, and the like are included in the specification solely for the purpose of providing a context for the present invention. It is not suggested or represented that any or all these matters form part of the prior art base or were common general knowledge in the field relevant to the present invention.
[0026] In this disclosure, whenever a composition or an element or a group of elements is preceded with the transitional phrase "comprising", it is understood that we also contemplate the same composition, element, or group of elements with transitional phrases "consisting of", "consisting", "selected from the group of consisting of, "including", or "is" preceding the recitation of the composition, element or group of elements and vice versa.
[0027] The present invention is described hereinafter by various embodiments with reference to the accompanying drawing, wherein reference numerals used in the accompanying drawing correspond to the like elements throughout the description. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiment set forth herein. Rather, the embodiment is provided so that this disclosure will be thorough and complete and will fully convey the scope of the invention to those skilled in the art. In the following detailed description, numeric values and ranges are provided for various aspects of the implementations described. These values and ranges are to be treated as examples only and are not intended to limit the scope of the claims. In addition, several materials are identified as suitable for various facets of the implementations. These materials are to be treated as exemplary and are not intended to limit the scope of the invention.
[0028] The present invention relates to Prediction and detection of liver cirrhosis disease through AI from secured block chain based liver cirrhosis dataset.
[0029] Patient data are maintained in a decentralized cloud-based blockchain database system. Every patient has their patient ID and Aadhar card Number so that Doctors can identify patients uniquely. All the patient's general data and medical test data are stored and updated in the block of block chain. Which can be available for all doctors worldwide with block chain security? So patients can also reach good doctors worldwide.
[0030] Some hilly and forest areas do have not good communication systems. In that case, we have small devices like the Mini Ultrasound Machine and Mini CBC test Machine which can be easy to relocate from one place to another place. These devices communicate with clouds through the internet so that unique patient medical test reports can be uploaded to the chain database.
[0031] If any patients have already done their medical tests can scan their medical reports by Nano-Net OCR Engine and upload them to the cloud. Text-based report data are trained by a Gated Recurrent Unit (GRU) to classify the Liver affected by Cirrhosis or Healthy then sent to the block of blockchain database. At the same time if the patient needs an ultrasound, then the ultrasound image data are uploaded to the cloud, classified by ResNet-50 and send results to the blockchain database as shown in Figure 1. When a Patient needs any doctor consultancy doctor can fetch data from the block of data block-chain. If the patient is in a remote area and can connect with the doctor, then an Encoder-Decoder and Attention Mechanism based Open-NMT system which is an Open Source translator helps to translate patients to understand doctor's prescription in their native language as shown in Figure 2.
[0032] For Optical Character Recognition (OCR), leveraging robust engines like Tesseract-OCR can be used. Instead of using a GRU classifier, more effective choices include LSTM and CNN-based classifiers, especially for text report analysis. When analysing of ultrasound image data, CNN and advanced architectures like ResNet models are suitable. For translation tasks, opting for the Hugging Face transformer system can be used.
[0033] Novel aspects of the invention: As data are storing in Decentralized in the block chain the security aspect of data will more effective and the Liver Cirrhosis patients can check their health in their home or nearer medical test center also patient can connect with doctors with worldwide with zero misguidance.
[0034] Various modifications to these embodiments are apparent to those skilled in the art from the description and the accompanying drawings. The principles associated with the various embodiments described herein may be applied to other embodiments. Therefore, the description is not intended to be limited to the 5 embodiments shown along with the accompanying drawings but is to be providing the broadest scope consistent with the principles and the novel and inventive features disclosed or suggested herein. Accordingly, the invention is anticipated to hold on to all other such alternatives, modifications, and variations that fall within the scope of the present invention and appended claims.
, Claims:CLAIMS
We Claim:
1) A system for predicting and detecting liver cirrhosis through artificial intelligence (AI) from a secure blockchain-based liver cirrhosis dataset, comprising:
- a decentralized cloud-based blockchain database system for storing patient data, wherein each patient is assigned a unique identifier including a patient ID and Aadhar card number;
- a miniaturized medical device for performing diagnostic tests, such as ultrasound and CBC (Complete Blood Count), capable of transmitting medical data to the blockchain database through internet connectivity;
- a Gated Recurrent Unit (GRU) or Long Short-Term Memory (LSTM) based classifier for processing text-based medical reports, classifying patients as liver cirrhosis-affected or healthy;
- a ResNet-50 based AI model for analyzing ultrasound images to detect liver cirrhosis;
- a Nano-Net OCR engine for scanning medical reports and converting text into machine-readable data for classification;
- an Open-NMT-based encoder-decoder translation mechanism to translate doctors' prescriptions into the patient's native language.
2) The system as claimed in claim 1, wherein patient data, including medical test results, are stored in block chain blocks, enabling secure access to authorized medical professionals worldwide for patient consultation and monitoring.
3) The system as claimed in claim 1, wherein the block chain database ensures data security, immutability, and privacy by employing cryptographic techniques, ensuring that patient data cannot be tampered with or accessed without proper authorization.
4) A method for classifying and storing liver cirrhosis diagnostic data on a blockchain-based system, the method comprising:
- Collecting patient medical test data, including ultrasound images and CBC results, using portable diagnostic devices;
- Scanning existing medical reports via Nano-Net OCR and uploading text data to the cloud-based blockchain;
- Classifying text-based medical reports using a GRU or LSTM-based AI classifier to determine whether the patient is affected by liver cirrhosis or is healthy;
- Analyzing ultrasound image data with a CNN-based model, including ResNet-50 architecture, for liver cirrhosis detection and uploading the results to the blockchain.
5) The system as claimed in claim 1, wherein blockchain-based system allows for remote access by medical professionals, enabling patients in remote or underdeveloped areas to receive diagnoses and consultations from doctors worldwide.
6) The system as claimed in claim 1, wherein patient's diagnostic data, including text reports and ultrasound images, are processed and uploaded in real-time using internet-connected portable devices, improving accessibility to healthcare for patients in geographically isolated areas.

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