Products

Products

We Brontobyte Analytics with the ML & DL models provide a modern optimized platform “DeepHealthCareVision™” an End-to-End Healthcare Analytics Platform.

DeepHealthCareVision ™

An advanced end-to-end healthcare interactive analytics platform with the following core capabilities: Automated natural language processing (NLP) of unstructured clinical notes, voice of the patient to text and the doctor notes, in order to store as structured, reportable data that can be rapidly searched and analysed intelligently.

Automated detection of tumour in various Radiology images such as Mammograms, Ultrasound, CT Scans, PETCT Scans, Magnetic Resonance Imaging (MRI) is very crucial as it provides information about abnormal tissues which is necessary for planning treatment. Automated tumour detection methods are developed as it would save radiologist time. The classification of Images into Normal and abnormal or benign and Malignant is difficult due to complexity and variance of tumours. The Medical Image Diagnostic Module will apply advanced AI algorithms and detects the tumour, its state/grade along with the decision making of advanced diagnostic suggestions.

Brontobyte has also an expertise in Digital pathology which has a dynamic image-based algorithm that empowers the acquisition, management and interpretation of pathological information generated from a digitized glass slide from the native source.

convolutional neural network explained

Radiology

deep learning tutorial

The increasing amount of data to be processed can influence how radiologists interpret images, from interpretation to merely detection and report generation. The time for evaluating clinical and laboratory contexts is clutched as too much time is spent on image analysis. The radiologist bounds to being only an image analyst. Radiology module of DeepHealthCareVision addresses this problem by providing automated image analysis capabilities using advanced Deep Learning and AI techniques

  • Supports Radiologist to locate the region of interest
  • Micro-calcification Identification
  • Reduce Turnaround time of the patient by 70%
  • Improve the accuracy and time taken using advanced Computer Vision and AI techniques
  • Reduce the number of misdiagnosed cases

Pathology

With pathology module, we aim to automatically and accurately perform the laborious image analysis tasks in a fraction of the time which gives doctors significant time back in their day for high-value work, such as identifying mitotic cells or screening benign tissue, and augment their capabilities to perform tasks like the identification of “cancer hotspots” and enables efficient, precise and more personalised care to the patients.

  • Improving the turnaround time in the Report Generation
  • Fullfilling the demand of the pathology services to every corner of the world
  • Identifing complex patterns in Histopathological images
convolutional neural network explained

Symptom Analysis

recurrent neural network pdf tutorial

Currently around the world 80% of all healthcare and life sciences data is unstructured, additionally health organizations have long recorded a variety of data, but have stored these inside disparate storage spaces. Doctors have long registered patient feedback and interactions in the form of hand written clinical notes, while frequently and unfortunately improperly coding these notes leaving important impactful information forgotten and locked away hidden inside the patient's medical record. Automated natural language processing (NLP) of unstructured clinical notes, voice of the patient to text and the doctor notes, in order to store as structured, reportable data that can be rapidly searched and analysed intelligently.

  • Proper storing and organisating of patient health records which helps in easy retrieval and analysis
  • Analyse the patient symptoms and suggest the necessary tests to be taken by the patient

Technologies

We Brontobyte Analytics with the ML & DL models provide a modern optimized platform “DeepHealthCareVision™” an End-to-End Healthcare Analytics Platform.

Data Ingestion & Management

  Ingestion, management on various type of medical data from various Clients.

Processing & Analysing

Processing and analysing various type of visual data using computer vision and other artificial intelligence algorithms.

AI Support

Statistical,mathematical, machine learning and the recent advancements in deep learning techniques (All types of AI techniques are supported).






Annotation and Validation

Annotation of all unlabelled data and verification/validation of predictions of various models by Radiologist, Pathologist & Oncologist.

Continuous Learning

Retraining of AI models with incremental validations/corrections and improvising their performance.

Insightful Consolidated Report Analysis

Analysing unseen medical images by invocation of one or many AI models on them and providing an consolidated and interactive report to the medical consultant.