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Artificial Intelligence Homepage

Silicon Valley investor paints dire picture for future of radiologists Claims they should no longer exist in a decade

AMA issues recommendations for accountability of AI in healthcare Aid in advancing quadruple aim

New algorithm better predictor of readmission following discharge, says study Final model drew predictions from 382 variables

Understanding 'data cleaning' in equipment service, and the tools used to do it Acquiring data is only the beginning, insights from AAMI

AI’s role in radiology — past, present, future What will it take to fully integrate machine learning into healthcare?

Startup raises over $6 million for early Alzheimer's detection AI With digital biomarkers, Altoida detects risk long before symptoms appear

Fujifilm to build new 'smart' facility for endoscope production Will leverage AI and IoT to enhance endoscope production

Google and Northwestern develop deep learning model for lung cancer detection Performed as well or even better than radiologists

Boston Children's Hospital teaming with GE Healthcare to develop radiology AI The first focus will reportedly be on brain scans

FDA clears Aidoc AI solution for flagging PE in chest CTs Speeding up the time between scan and diagnosis

Pooja Rao

Smart intelligence for trauma caregivers

By Pooja Rao

Artificial intelligence (AI) has been transforming the world in many ways, and the field of medicine is no exception. It has been invaluable in aiding the diagnosis and treatment of many life-threatening conditions. In fact, the research firm CB Insights reports that AI-driven healthcare startups had raised $4.3B across 576 deals between 2013 and 2018, overtaking all other industries in AI deal activity.

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The use of AI and machine learning technologies for healthcare is not a new concept. FDA-approved algorithms were used as early as 1998, for detecting cancerous cells. The key difference today is that the hardware and the algorithms have improved substantially, which enables us to deliver faster, innovative and accessible healthcare solutions. AI has now been deployed for a wide range of medical needs, from streamlined workflows to robot-assisted surgeries

Why you should know about TBI
March was Traumatic Brain Injury (TBI) awareness month. TBI occurs due to sudden and excessive force on the skull, and being aware is critical as it could happen to anyone, at any time. In the US, around 137 people die from a TBI every day. From bad falls and vehicle collisions to violent assaults, or even tumors, TBIs are incredibly dangerous. Children are often the most susceptible, and the effects of such an injury to their developing brains can, in many cases, become permanent.

Patients who’ve had serious head injuries may face permanent changes in personality, physical abilities and thinking processes. This is because TBI patients’ brains show decreased activity in the prefrontal cortex, temporal lobes and cerebellum – the regions that govern self-control of mood and behavior, memory formation and coordinated.

A head injury can occur even when there are no visual signs of injury on the head itself, and therefore it can sometimes be hard to assess its level of seriousness. The head has more blood vessels than any other part of the body, so any bleeding on the brain’s surface or within, is a serious concern. Some minor head injuries bleed a lot, while some major injuries don’t bleed at all, therefore it’s critical all head injuries be assessed by a doctor and treated immediately. TBI diagnosis in an emergency unit is usually done through a CT scan, which enables the doctor to assess the extent of the injury and determine the need for surgery. A detailed MR scan is followed up once the patient is stabilized.

AI to the rescue
Studies have proved that TBI patients’ recovery depends heavily on the speed to initiate treatment. Patients treated within 90 minutes of the injury have a better chance of improving within 24 hours and have better outcomes within a 3-month timeframe.
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Artificial Intelligence Homepage


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