Building Bridges
To
Better Health
DashamlavAI: AI-powered Analytics & Digitization for Breakthrough Oncology Care
Better Health
"Model Training to Predictive Analysis "
Through OncFlow, the entire pipeline—from data collection and model training to deployment—is handled precisely and integrated into your existing systems. Once a model is deployed, it becomes a powerful tool for your entire team, empowering them to make informed decisions quickly and accurately, leveraging the capability of Real-World Data (RWD) and evidence (RWE).
This seamless integration ensures that our predictive analysis capabilities not only provide immediate benefits but also evolve with your practice to continuously meet your patients' needs and enhance your clinical efficacy.
Furthermore, additional models, such as those for assessing DIBH eligibility, can be built to aid decision-making in real-time as data is captured.
Our live model prediction feature for DIBH eligibility provides instant feedback during assessment, potentially saving evaluation days and streamlining patient care.
These tools enhance clinical practice and empower users to effectively harness AI for their specific needs, making them truly AI-enabled.
informed decisions
enhance your clinical efficacy
assessing DIBH eligibility
decision-making in real-time
Real-World Data (RWD)
Real-World evidence (RWE)
Dashamlav is proud to offer an advanced predictive analysis service that leverages Real World clinical and imaging data and integrates them seamlessly within routine clinical workflows. As part of our OncFlow platform, images and associated clinical data are collected and utilized to develop sophisticated machine learning and deep learning models.
These models are meticulously crafted from rich datasets to provide critical insights for patient management and decision-making in cancer care.
As users accumulate sufficient data, Dashamlav's AI capabilities extend even further. Advanced AI models can be developed to make data entry more intelligent and efficient by predicting form fields based on historical data.
As users input data, the system can anticipate and fill in related fields, significantly speeding up the data entry process and reducing manual effort.
leverages clinical and imaging data
machine learning and deep learning models
critical insights for patient management
decision-making in cancer care
intelligent and efficient
reducing manual effort
The deployment of these AI models enables a transformative approach to understanding and managing patient data, offering predictions that enhance treatment planning and patient outcomes hence creating Real World Evidence (RWE).
Beyond generic solutions, Dashamlav provides a bespoke advisory service. This service guides users through the process of creating custom AI models tailored to specific clinical questions.
Whether you need to predict treatment responses or assess eligibility for specific interventions, our team supports you in leveraging your data to build models that address your unique challenges.
transformative approach
offering predictions
treatment planning
patient outcomes
custom AI models
predict treatment responses
Base Model is supported by our CloudHD which brings the best of Data security safety, privacy, business continuity and other important aspects of Global standards of Data protection.
Our Process
01
Register
03
Care Plan
02
Diagnosis
04
Simulation
Our Process
01
Register
02
Diagnosis
03
Care Plan
04
Simulation
Dashboard
Shaping
healthcare
heroes
News & Insights
SCENARIO : OVERALL DATA ENTRY EFFICIENCY REAL WORLD IMPACT: Overall Data Entry Easy & Highly Efficient Across Care Delivery Scenario : Data …
SCENARIO : PUBISHABLE RESARCH QUICK & INSIGHTFUL REAL WORLD IMPACT: High Quality Publishable Research based on Own DataScenario: The collation of acute …
SCENARIO : ONCOLOGIST WORKLOAD REDUCTION REAL WORLD IMPACT: Higher Patient Thruput, Higher Patient Facetime, Higher Quality Care Delivery Impact: From the oncologist’s …
SCENARIO : OPD WAITING TIME REDUCTION REAL WORLD IMPACT: Higher number of Patients seen by Specialist, Care Delivery to Patient Assess impact …
SCENARIO : TIME SAVED IN ROOT CAUSE ANALYSIS REAL WORLD IMPACT: On-Time Corrective Action, Uninterrupted Workflow, Machine Uptime, Care Delivery to Patient …
SCENARIO : IMPROVED QUALITY OF CARE BY ELIMINATING CARE PROVIDER PAIN POINTS & PATIENT PAIN POINTS REAL WORLD IMPACT: Standardized Care Protocols …
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