Tuesday December 10, 2019

Government to launch a scheme that will offer free diagnostic tests

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By NewsGram Staff Writer

The Central government has come up with a scheme that will offer free diagnostic tests to people visiting public health centers.

A bench of experts has prepared a list of diagnostic tests which are regarded as essential for all categories of health facilities. The Health Ministry has also contacted some of the biggest names in the diagnostic sector like Dr. Lal PathLabs, Quest Diagnostics, Mahajan Imaging and Star Imaging.

The scheme would improve the diagnostic infrastructure in government hospitals. Under the scheme, private health service providers will be engaged for the collection of blood samples, analysis and reporting at places where the government infrastructure is lacking. CT scan services will also be developed at district level under public-private partnership.

This action taken by the Centre would not only reduce the health expenditure of the masses but according to a newspaper report, it would also promote the diagnostics and reagents sectors, whose share currently amounts to only 20% in the medical technology market.

However, the initiative has also drawn flak from a lot of people. Sakthivel Selvaraj, a health economist told the Times of India, “With a slashed health budget and no allocation in the budget for the scheme, where will they find additional resources for this? Tamil Nadu and Rajasthan are already providing diagnostic facilities more efficiently without outsourcing. Why not follow that model? Why follow a model of outsourcing that has failed in several states like Bihar and Chhattisgarh? Outsourcing only adds to the cost.”

According to the report, some public health technology experts felt that selective outsourcing has been shown to work in certain other technology intensive areas such as ambulance care. The development of these technologies would not have been possible without the assistance of private sector.

“Experience suggests that measured formula-based centralized outsourcing is recommended only for ancillary services that are technology intensive,” told one such expert to TOI.

Many people have questioned whether the outsourcing would lead to private sectors extorting extravagant charges for their services. A doctor working in a railway hospital told NewsGram, “To prevent private sectors from exploiting people, the government should fix price rates for the diagnostic services. This scheme proposed by the government should follow the same model of Central Government Health Scehme (CGHS) which engages with only those private hospitals which agree to follow the price rate set by it. ”

Next Story

AI Can Better Help Doctors to Identify Cancer Cells in Human Body

The process of manually identifying all the cells in a pathology slide is extremely labor intensive and error-prone

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Cancer
The AI algorithm helps pathologists obtain the most accurate Cancer cell analysis - in a much faster way. Pixabay

Researchers at University of Texas Southwestern have developed a software tool that uses Artificial Intelligence (AI) to recognize Cancer cells from digital pathology images – giving clinicians a powerful way of predicting patient outcomes.

The spatial distribution of different types of cells can reveal a cancer’s growth pattern, its relationship with the surrounding microenvironment, and the body’s immune response.

But the process of manually identifying all the cells in a pathology slide is extremely labor intensive and error-prone.

“To make a diagnosis, pathologists usually only examine several ‘representative’ regions in detail, rather than the whole slide. However, some important details could be missed by this approach,” said Dr. Guanghua “Andy” Xiao, corresponding author of a study published in EbioMedicine.

A major technical challenge in systematically studying the tumor microenvironment is how to automatically classify different types of cells and quantify their spatial distributions.

The AI algorithm that Dr Xiao and his team developed, called “ConvPath”, overcomes these obstacles by using AI to classify cell types from lung cancer pathology images.

Cancer
Researchers at University of Texas Southwestern have developed a software tool that uses Artificial Intelligence (AI) to recognize Cancer Cells from digital pathology images – giving clinicians a powerful way of predicting patient outcomes. Pixabay

The ConvPath algorithm can “look” at cells and identify their types based on their appearance in the pathology images using an AI algorithm that learns from human pathologists.

The algorithm helps pathologists obtain the most accurate cancer cell analysis – in a much faster way.

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“It is time-consuming and difficult for pathologists to locate very small tumour regions in tissue images, so this could greatly reduce the time that pathologists need to spend on each image,” said Dr Xiao. (IANS)