Sunday December 8, 2019
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Hackers can Easily Change Patient’s MRI, CT Scan Results

The researchers suggested several solutions, such as enabling encryption between the hosts in the hospital’s radiology network, digital signatures with a secure mark on each scan or hidden digital watermarks

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Representational image.

Patients’ CT and MRI scan results can be easily changed by hackers, thereby deceiving radiologists and Artificial Intelligence (AI) algorithms that diagnose malignant tumours, Israeli researchers have warned.

The researchers from the Ben-Gurion University (BGU) showed that hackers could access to add or remove medical conditions from lung cancer scans for the purposes of insurance fraud, ransom and even murder, Xinhua news agency reported.

As part of the attack, the hacker has full control over the number, size and location of the cancers while preserving the anatomy from the original, full resolution three-dimensional (3D) image.

To prove the feasibility of the attacks, the researchers broke with permission into an actual hospital network to intercept all CT (computed tomography) scans.

Although the hospital internal network is not connected to the internet, hackers can access it via the hospital’s WiFi or physical access to the infrastructure, the researchers said.

hackers, hacking group, military
iDefense said the hackers are likely affiliated with a group known as MUDCARP, and also referred to as TEMP.PERISCOPE, Periscope and Leviathan. Pixabay

To inject and remove medical conditions, the researchers used a deep learning neural network called a generative adversarial network (GAN), which has been used in the past to generate realistic imagery, such as portraits of non-existent people.

After the “attack” the radiologists at the hospital misdiagnosed 99 per cent of the scans showing malignant tumours, and 94 per cent of altered images with cancerous images removed.

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After the radiologists were informed about the attack, they still misdiagnosed 60 per cent of altered scans falsely showing tumours and 87 per cent of those falsely showing no sign of the tumour, the report showed.

The researchers suggested several solutions, such as enabling encryption between the hosts in the hospital’s radiology network, digital signatures with a secure mark on each scan or hidden digital watermarks. (IANS)

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AI To Predict If Chemotherapy Useful For Lung Cancer Or Not

Artificial Intelligence to determine if chemotherapy is working in lung cancer

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Chemotherapy for lung cancer
Scientists will use AI to know if chemotherapy is useful to cure lung cancer. Pixabay

Scientists who have pioneered the use of Artificial Intelligence (AI) to predict whether chemotherapy will be successful, can now determine which lung-cancer patients will benefit from expensive immunotherapy.

Researchers used AI to find previously unseen changes in patterns in CT scans taken when the lung cancer is first diagnosed compared to scans taken after the first 2-3 cycles of immunotherapy treatment.

And, as with previous work, those changes have been discovered both inside–and outside — the tumour, a signature of the lab’s recent research.

“The research really seems to be reflecting something about the very biology of the disease, about which is the more aggressive phenotype, and that’s information oncologists do not currently have,” said Anant Madabhushi, whose Center for Computational Imaging and Personalized Diagnostics (CCIPD) has become a global leader in the detection, diagnosis and characterization of various cancers by using AI.

Currently, only about 20 per cent of all cancer patients will actually benefit from immunotherapy, a treatment that differs from chemotherapy in that it uses drugs to help your immune system fight cancer, while chemotherapy uses drugs to directly kill cancer cells.

Chemotherapy and immunotherapy
Only about 20 per cent of all cancer patients will actually benefit from immunotherapy, a treatment that differs from chemotherapy. Wikimedia Commons

Madabhushi said the recent work by his lab would help oncologists know which patients would actually benefit from the therapy, and who would not.

“Even though immunotherapy has changed the entire ecosystem of cancer, it also remains extremely expensive — about $200,000 per patient, per year,” Madabhushi said.

“That’s part of the financial toxicity that comes along with cancer and results in about 42 per cent of all new diagnosed cancer patients losing their life savings within a year of diagnosis”.

The new research, led by co-authors Mohammadhadi Khorrami and Prateek Prasanna, along with Madabhushi and 10 other collaborators from six different institutions was published in the journal Cancer Immunology Research.

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Prasanna said the study also showed that the results were consistent across scans of patients treated at two different sites and with three different types of immunotherapy agents.

“This is a demonstration of the fundamental value of the programme, that our machine-learning model could predict response in patients treated with different immune checkpoint inhibitors,” he added. (IANS)