The common bottlenecks which might slow down your business growth
Pathologists in the general field, with most pathologists choosing a niche area of operation.
The lack focus on the molecular basis of the disease, with an approach that is too narrow and does not address the situation holistically.
Minimal interaction between the physician/ clinician and the pathologist makes meaningful collaboration and comprehension difficult.
Cumbersome procedures are playing their part in creating complications in the testing process.
Pathologists are not involved in clinical processes and patient examination, which interferes with holistic diagnosis
The financial constraints that come with lab testing hampers the quality of pathology
Conduct automated and holistic diagnosis, with a minimal likelihood of error, with AI for medical diagnosis-related technology
The efficiency of lab testing with artificial intelligence is undeniably higher through the use of intelligent machines that are embedded with software for digital imaging. When it comes to diagnostics, artificial intelligence based diagnostics through AI-based medical diagnosis devices offer a shorter turnaround time than traditional microscopic testing.
Through AI-based medical diagnosis, pathologists can send data and images to different specialists around the globe that enhances research, diagnosis and collaborative diagnosis, without the need to physically move the specimen from one location to another. The automated features of AI in pathology, including AI for medical tests, reduce manual errors that are often witnessed in physical inspections.
The automated nature of digital pathology is empowered with artificial intelligence that allows a pathologist to increase their productivity by a considerable margin through the reduction of manual process and mundane sections of pathology report generation. Machine learning makes diagnosis more accurate and prompt.
Lab testing with artificial intelligence translates into intelligent algorithms that are capable of identifying general and specific patterns that can then offer logical and reliable predictions toward patient diseases. AI-based medical diagnosis uses automated diagnostic devices to offer a shorter turnaround time then traditional microscopic testing.
AI-based medical diagnosis causes an instant transformation, wherein pathologists in the digital realm are no longer dealing with glass, but with pixels that can be sent to any part of the world for specialized examination. Through image analysis algorithms, AI in medical testing allows for automated analysis that is generated through the basis of research and recorded data in the software.
AI solutions leverage the predictive analytics technology to assist clinicians to identify disease vulnerability prior to its onset. This creates a culture of preventive care as opposed to remedial care. Through intelligent machine learning, patients who are prone to a certain illness are flagged and therefore, capture the attention of the pathologist who can then advice long term care.
OSP has worked with Stephen to create a mobile health application offering 'Doctor on Demand'. This mhealth solution is based on the Uber model to enhance the availability of health access in the US.
AI in medical diagnosis can play a vital role in pathologist by accurately identifying rare objects in the body fluids such as blood and urine, as well as tissues. Abnormalities in body fluids and tissue can be automatically detected using AI in medical diagnosis solutions.
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AI in medical diagnosis can automatically detect skin cancer after being trained to classify skin lesion images as benign lesions or malignant skin cancers. The initial screening can help providers in better clinical decision making in time.
How we do it
AI in medical diagnosis can be customized to detect abnormalities and make an accurate diagnosis in time. Identifying cardiovascular abnormalities, detecting bone fractures, neurological disease diagnosis, flagging thoracic complications and can be performed with AI in medical diagnosis.
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Segmenting brain tumors in MR images can be achieved with AI in medical diagnosis software solutions. computer-aided brain tumor diagnosis and surgical planning can accurately and efficiently make tumor segmentation and measure the size of tumors that help in clinical decision making and offer the best and timely care to the patients.
How we do it
A breakthrough technology in the immunotherapy domain, OSP Labs leverages AI algorithms to offer suggestions as to the ways in which the patient’s own immunity can be used to heal or prevent ailments. This is executed through the complex analysis of tissue phonemics and changes in biochemical traits, through genetic mutation and environmental factors are identified. The combination of AI and medical diagnosis offers image analysis based diagnosis that is radically superior in accuracy through standardization and automation features that are enabled into our computational pathology technology.
These are solutions that use neural elements to make the system identify objects that have been rarely or never seen. Through advanced AI and medical diagnosis algorithms, these objects are then analyzed and highlighted to the pathologist, along with a detailed account. The process is further enhanced through a suggested translation of the implication of the identified object.
Transmitting digital material from one end of the world to another now comes bereft of constraints such as tampering. Through this association, the possibilities of collaboration are extended and lab growth is enhanced through increased access to specialists around the world. This AI solution offers holistic diagnosis by expanding its reach to capture the full-spectrum of the research and resources available.
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