Tuesday March 31, 2020

New AI Algorithms Can Predict Drug Response Lung Cancer

AI can better predict drug response to lung cancer therapies

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Lung cancer
With AI, lung cancer imaging can move from an inherently subjective tool to a quantitative and objective asset for precision medicine approaches. Pixabay

Researchers have used Artificial Intelligence (AI) to train algorithms and predict tumour sensitivity in three advanced non-small cell lung cancer therapies which can help predict more accurate treatment efficacy at an early stage of the disease.

The researchers at Columbia University’s Irving Medical Center analyzed CT images from 92 patients receiving drug agent nivolumab in two trials; 50 patients receiving docetaxel in one trial; and 46 patients receiving gefitinib in one trial.

To develop the model, the researchers used the CT images taken at baseline and on first-treatment assessment.

“The purpose of this study was to train cutting-edge AI technologies to predict patients’ responses to treatment, allowing radiologists to deliver more accurate and reproducible predictions of treatment efficacy at an early stage of the disease,” explained Laurent Dercle, associate research scientist at the Columbia University Irving Medical Center.

Lung cancer
Researchers have used Artificial Intelligence (AI) to train algorithms and predict tumour sensitivity in three advanced non-small cell lung cancer therapies. Pixabay

Radiologists currently quantify changes in tumour size and the appearance of new tumour lesions. However, this type of evaluation can be limited, especially in patients treated with immunotherapy, who can display atypical patterns of response and progression.

“Newer systemic therapies prompt the need for alternative metrics for response assessment, which can shape therapeutic decision-making,”
Dercle said in a paper appeared in the journal Clinical Cancer Research.
The researchers used machine learning to develop a model to predict treatment sensitivity in the training cohort.

Each model could predict a score ranging from zero (highest treatment sensitivity) to one (highest treatment insensitivity) based on the change of the largest measurable lung lesion identified at baseline.

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“We observed that similar radiomics features predicted three different drug responses in patients with advanced non-small cell lung cancer (NSCLC) ,” Dercle said.

“With AI, cancer imaging can move from an inherently subjective tool to a quantitative and objective asset for precision medicine approaches,” he added. (IANS)

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Know About Where Do Employees Actually Gaze At During Video Calls

For the study, published in the journal Attention, Perception & Psychophysics, the team compared fixation behaviour in 173 participants under two conditions

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Video Chat
The phenomenon known as "gaze cueing," a powerful signal for orienting attention, is a mechanism that likely plays a role in the developmentally and socially important wonder of "shared" or "joint" attention where a number of people attend to the same object or location. Pixabay

 As more and more people use video conferencing tools to stay connected in social distancing times, neuroscientists from Florida Atlantic University have found that a person’s gaze is altered during tele-communication if they think that the person on the other end of the conversation can see them.

The phenomenon known as “gaze cueing,” a powerful signal for orienting attention, is a mechanism that likely plays a role in the developmentally and socially important wonder of “shared” or “joint” attention where a number of people attend to the same object or location.

“Because gaze direction conveys so much socially relevant information, one’s own gaze behaviour is likely to be affected by whether one’s eyes are visible to a speaker,” said Elan Barenholtz, associate professor of psychology. For example, people may intend to signal that they are paying more attention to a speaker by fixating their face or eyes during a conversation.

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“Conversely, extended eye contact also can be perceived as aggressive and therefore noticing one’s eyes could lead to reduced direct fixation of another’s face or eyes. Indeed, people engage in avoidant eye movements by periodically breaking and reforming eye contact during conversations,” explained Barenholtz.

People are very sensitive to the gaze direction of others and even two-day-old infants prefer faces where the eyes are looking directly back at them. Social distancing across the globe due to coronavirus (COVID-19) has created the need to conduct business “virtually” using Skype, web conferencing, FaceTime and any other means available.

For the study, published in the journal Attention, Perception & Psychophysics, the team compared fixation behaviour in 173 participants under two conditions: one in which the participants believed they were engaging in a real-time interaction and one in which they knew they were watching a pre-recorded

The researchers wanted to know if face fixation would increase in the real-time condition based on the social expectation of facing one’s speaker in order to get attention or if it would lead to greater face avoidance, based on social norms as well as the cognitive demands of encoding the conversation.

Online, Webinar, Teacher, Conferencing, Tutor, Video
As more and more people use video conferencing tools to stay connected in social distancing times, neuroscientists from Florida Atlantic University have found that a person’s gaze is altered during tele-communication if they think that the person on the other end of the conversation can see them. Pixabay

Results showed that participants fixated on the whole face in the real-time condition and significantly less in the pre-recorded condition. In the pre-recorded condition, time spent fixating on the mouth was significantly greater compared to the real-time condition. There were no significant differences in time spent fixating on the eyes between the real-time and the pre-recorded conditions. To simulate a live interaction, the researchers convinced participants that they were engaging in a real-time, two-way video interaction (it was actually pre-recorded).

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When the face was fixated, attention was directed toward the mouth for the greater percentage of time in the pre-recorded condition versus the real-time condition. “Given that encoding and memory have been found to be optimized by fixating the mouth, which was reduced overall in the real-time condition, this suggests that people do not fully optimize for speech encoding in a live interaction,” the authors wrote. (IANS)