Artificial intelligence plays an increasingly significant role in analyzing medical images, such as computed tomography (CT), magnetic resonance imaging (MRI), and X-rays. Advanced AI algorithms enable the detection of even the smallest anomalies that might escape the human eye, significantly improving diagnostic accuracy. Automated image processing also allows for faster results, which is crucial in situations requiring immediate intervention. Medical personnel benefit from more detailed and precise information about patients’ health, supporting accurate therapeutic decisions and enabling better monitoring of treatment progress. As a result, AI not only enhances the efficiency of healthcare professionals but also improves the overall quality of medical care.
Artificial Intelligence Supporting Medical Professionals
• Medical Diagnostics – AI utilizes algorithms and deep machine learning to analyze test results and images from sources like CT scans, X-rays, and MRIs, reducing the time needed for diagnosis.
• Telemedicine – AI is revolutionizing telemedicine by introducing automated diagnostic systems that alleviate the workload for doctors and accelerate the diagnostic process. Many platforms, like Receptomat.pl, offer traditional teleconsultations, enabling communication with physicians and issuing e-prescriptions, e-sick leaves, or test referrals.
• Personalized Treatment – AI leverages patient data, including medical history, genetic tests, and lifestyle factors, to predict treatment effectiveness and tailor therapies to individual needs, enhancing outcomes and minimizing adverse effects.
• Support for Clinical Research – AI aids in analyzing clinical trial data and identifying patterns that could lead to new therapies. This reduces research time and lowers costs.
• Health Monitoring – AI facilitates remote monitoring of patient's vital signs, such as blood pressure, glucose levels, and heart rate, allowing for the early detection of health issues. Results from wearable devices like smart bands or smartwatches can be shared with doctors via medical platforms.
Computer Vision Solutions on ONESTEP AI Platform
The ONESTEP AI platform supports the development of models for implementing AI algorithms in diagnostic imaging. Key applications of ONESTEP AI include:
• Image Segmentation - This process divides medical images into smaller, homogenous regions for separate analysis. It isolates specific anatomical or pathological structures, such as organs, tissues, tumors, or lesions. By enhancing the precision of image segmentation, AI enables a more accurate assessment of a patient’s condition, which is vital for diagnostics. Advanced AI algorithms make segmentation increasingly precise and efficient, supporting clinicians in making informed decisions.
• Image Classification - Image classification assigns portions of an image to predefined categories based on features like texture, shape, or intensity. In medical diagnostics, this might involve distinguishing between healthy and pathological tissues. For example, AI can classify images as showing healthy tissue or cancerous tissue, enabling faster and more accurate disease diagnosis, such as identifying cancer. Automated image classification also helps clinicians assess the severity of a condition.
• Text Analysis - Analyzing medical texts, including image reports and other documents related to cancer diagnoses, facilitates the automatic extraction of critical information such as diagnoses, treatment recommendations, and test results. Text analysis supports healthcare professionals by providing faster access to key data, especially in complex cases. With AI-driven tools, large datasets can be processed quickly and efficiently, leading to better treatment strategies and monitoring patient progress in therapy.
ONESTEP AI Platform by Intratel
Equipped with advanced computer vision algorithms, Intratel's ONESTEP AI platform offers state-of-the-art tools for building models that support medical image diagnostics. By analyzing medical images such as X-rays, CT scans, dermatoscopic imaging, and MRIs, models trained on the platform can quickly and accurately identify pathological changes.
Computer vision algorithms can detect subtle differences in tissues, enabling the early identification of diseases. For example, models can detect tumors, inflammatory changes, or other abnormalities that traditional methods might overlook. Automating image analysis with ONESTEP AI not only significantly reduces the time needed to develop models for diagnostic purposes but also makes advanced AI technology accessible to users without backgrounds in fields like computer science or data science.
Trained models can also assist healthcare professionals in classifying different types of abnormalities, and distinguishing between healthy and pathological tissues.
Additionally, ONESTEP AI enables the creation of models for image segmentation, allowing precise delineation of areas of interest, such as tumors, and assessing their size and shape. Integration with hospital systems ensures seamless incorporation of analysis results into medical documentation, providing doctors with easy access to results and patient histories.
The algorithms embedded in ONESTEP AI can learn from data collected across various cases, improving their accuracy with each analysis. With these advanced capabilities, the ONESTEP AI platform enhances diagnostic precision and treatment efficiency, offering cutting-edge support for medical imaging applications.
Key Features of ONESTEP AI in Medical Image Analysis
2. Image Segmentation – ONESTEP AI automatically divides images into smaller segments, allowing for detailed analysis of specific areas. This feature enables the training of models that can precisely extract elements such as tissues, organs, or pathological changes, significantly simplifying the diagnostic process.
3. Detection and Classification – User-trained models can automatically detect and classify abnormalities in images, such as tumors, cysts, or cancerous changes, and assign them to appropriate categories. This capability can facilitate early disease detection, enabling timely diagnostic and therapeutic actions.
4. Early Diagnosis – With advanced image analysis, models trained using ONESTEP AI can identify pathological changes at early stages, increasing the chances of effective treatment, especially for cancer. Automated recognition of subtle changes, which may go unnoticed with traditional methods, accelerates the diagnostic process, supporting prompt and informed decision-making.
6. Self-Learning and Data Adaptation – ONESTEP AI is a system capable of building models that learn from accumulated data, continuously improving the accuracy of its algorithms with each new case. This feature enhances the system's precision and effectiveness in analyzing medical images over time.
7. Support for Clinical Decision-Making – ONESTEP AI allows for the creation of models that assist physicians in interpreting diagnostic results, aiding in making accurate therapeutic decisions. The precise analysis of images helps determine the extent of the disease and select the most appropriate treatment method.
8. Scalability and Flexibility – The ONESTEP AI platform is both flexible and scalable, meaning it can be tailored to the needs of various medical facilities, regardless of size. It can be implemented in hospitals, clinics, or medical offices, supporting a wide range of imaging modalities and analysis requirements.
9. Compliance and Data Security – ONESTEP AI adheres to all applicable standards and regulations for the protection of medical data, ensuring full compliance with frameworks such as GDPR, ISO 27001, and ISO 27018. The platform guarantees the security and confidentiality of information processed on the ONESTEP AI system.
Pricing
| Standard Plan | Professional Plan |
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Building on the Standard Plan, the Advanced Plan includes:
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| Monthly Fees for Platform Access (Per User) | |
| 1.599 PLN + VAT | 4.119 PLN + VAT |
| Additional Monthly Fees – Resources | |
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Additional Storage: 100GB - 16,06 PLN + VAT GPU Processing Resources: - 26,65 PLN + VAT /h |
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