Source: The Deep View: AI for Good: Traumatic brain injuries: Quote: A recent, systematic, review of algorithmic approaches to TBI diagnosis found that “each algorithm has a strong ability to automatically identify and quantify important CT findings caused by TBI. (Personal comment before reading this I can vouch for another aspect. Researching family lore via Grok3 and it really fills in gaps I had never quite grasped). The speed of roll out of data incredible. If you are thinking of writing a book, take your headings and input to Grok3 AI …

Posted on March 21, 2025 by michelleclarke2015
AI for Good: Traumatic brain injuries

Source: Unsplash

Traumatic brain injury (TBI) is often described as “the silent epidemic” for a simple confluence of reasons: a steady lack of awareness of and research into it, its widespread reach — impacting nearly 70 million people each year — and its damaging, sometimes lethal, impact to its victims. 

The causes of TBI are varied: car accidents, falls or, generally, blows to the head. And the resulting levels of TBI are varied, as well, ranging from mild concussions to severe injuries that can lead to permanent cognitive damage. 

The details: In the midst of this crisis, one that kills nearly 70,000 Americans every year, researchers are increasingly studying the diagnostic impact of specifically trained and tuned machine learning algorithms. And though complicated, the integration is promising. 

The predominant means of diagnosing TBI today involves the manual review of CT brain scans, a process that is necessarily time-consuming. 

A recent, systematic, review of algorithmic approaches to TBI diagnosis found that “each algorithm has a strong ability to automatically identify and quantify important CT findings caused by TBI.

”Why it matters: The implication of this is that a combination of different machine learning algorithms can work as a “good supporting tool” to reduce the workload of radiologists and clinicians, while boosting the odds of early detection. 

Still, it’s early days, here. The algorithms — both in machine learning and deep learning — have certain limitations, namely related to algorithmic bias resulting from data sets that don’t completely capture the full range of TBI. Much more research needs to be done for clinicians to see the introduction of a reliable, usable tool.  


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About michelleclarke2015

Life event that changes all: Horse riding accident in Zimbabwe in 1993, a fractured skull et al including bipolar anxiety, chronic fatigue …. co-morbidities (Nietzche 'He who has the reason why can deal with any how' details my health history from 1993 to date). 17th 2017 August operation for breast cancer (no indications just an appointment came from BreastCheck through the Post). Trinity College Dublin Business Economics and Social Studies (but no degree) 1997-2003; UCD 1997/1998 night classes) essays, projects, writings. Trinity Horizon Programme 1997/98 (Centre for Women Studies Trinity College Dublin/St. Patrick's Foundation (Professor McKeon) EU Horizon funded: research study of 15 women (I was one of this group and it became the cornerstone of my journey to now 2017) over 9 mth period diagnosed with depression and their reintegration into society, with special emphasis on work, arts, further education; Notes from time at Trinity Horizon Project 1997/98; Articles written for Irishhealth.com 2003/2004; St Patricks Foundation monthly lecture notes for a specific period in time; Selection of Poetry including poems written by people I know; Quotations 1998-2017; other writings mainly with theme of social justice under the heading Citizen Journalism Ireland. Letters written to friends about life in Zimbabwe; Family history including Michael Comyn KC, my grandfather, my grandmother's family, the O'Donnellan ffrench Blake-Forsters; Moral wrong: An acrimonious divorce but the real injustice was the Catholic Church granting an annulment – you can read it and make your own judgment, I have mine. Topics I have written about include annual Brain Awareness week, Mashonaland Irish Associataion in Zimbabwe, Suicide (a life sentence to those left behind); Nostalgia: Tara Hill, Co. Meath.
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