A SUPER-powered WP Engine Atlas Test Site

Joe&#039;s Atlas Experimentation Site

Researchers have unveiled a new AI-powered avatar platform — one making use of artificial intelligence (AI) technology — that aims to help people with <a href="https://alsnewstoday.com/what-is-als/">amyotrophic lateral sclerosis</a> (ALS) to communicate, even when the neurodegenerative disease progresses to the point that speaking and moving become difficult or impossible.
The platform was developed through a collaboration between tech companies <a href="https://www.lenovo.com/us/en/">Lenovo</a> and <a href="https://www.deepbrain.io/">DeepBrain AI</a>, as well as the <a href="https://www.scottmorganfoundation.org/">Scott-Morgan Foundation</a>, a nonprofit that focuses on assistive technologies.
“This is a fantastic example of the untapped potential of generative AI to empower individuals and build a more inclusive future,” Scott Tease, vice president and general manager of high-performance computing and AI at Lenovo, said in a <a href="https://www.businesswire.com/news/home/20240109052328/en/AI-Powered-Avatar-from-Lenovo-DeepBrain-AI-and-the-Scott-Morgan-Foundation-Creates-New-Communication-Possibilities-for-People-with-Severe-Disabilities">press release</a>.
The AI-powered platform was revealed at CES 2024, a tech showcase being held Jan. 9-12 in Las Vegas. Andrew Morgan, CEO of the Scott-Morgan Foundation, said the nonprofit&#8217;s vision “is built on a commitment to ensuring a universal right to thrive through technology.&#8221;
&#8220;AI is accelerating work we began years ago, and our brilliant collaborators are helping us completely change the accessibility landscape,&#8221; Morgan said. &#8220;Collectively, we are lighting a beacon for what’s possible—not just for people with ALS, but for everyone.”
[recommended-reading id=87020]
<h3>AI-powered assistive tech platform aims to help those with severe disease</h3>
ALS is characterized by the progressive death and degeneration of the nerve cells that control voluntary movement. This eventually leads to paralysis, which can make it hard for people with the condition to communicate.
DeepBrain has been developing AI-based avatars — video portrayals that capture the look and personality of people. As part of an ongoing collaboration with the Scott-Morgan Foundation, Lenovo spearheaded an effort to adapt this technology to help people with ALS and other disease maintain communication abilities even when they can no longer do so with their own bodies.
&#8220;Leveraging our expansive solutions portfolio and in-house expertise, we love finding these opportunities to reimagine what’s possible and help solve humanity’s greatest challenges,&#8221; Tease said.
Eric Jang, CEO of DeepBrain AI, said his company&#8217;s goal is to use AI-powered tech to &#8220;enable hyper-realistic avatars for everyone.”
“We are constantly amazed at how our partners and clients think of new ways to use AI-generated video,&#8221; Jang said. &#8220;Lenovo had the foresight to share their vision on how this technology could be implemented as a component of an assistive technology platform.”
As a proof-of-concept, Erin Taylor — a 24-year-old woman who last year was diagnosed with ALS — underwent full-body video capture at a studio. That was then used to <a href="https://www.youtube.com/watch?v=4LxqB6gS7Dc&amp;feature=youtu.be">create an avatar for her</a> that offers 96% true-to-life accuracy. The avatar was debuted at CES 2024.
Taylor, who lives in California with her mother, was pursuing a career in botany and forestry when she experienced &#8220;a brief series of escalating symptoms&#8221; that resulted in her diagnosis.
“Feeling so devastated and lost, we were grateful to the Scott-Morgan Foundation for inviting us to help build something new and shape the future,” Taylor said.
[quote=&#8221;center&#8221;]The avatar is incredible, but what matters most to me is that this technology could help change the lives of many more people facing ALS or other diseases — a way of showing how bright the future can still be.[/quote]
Lenovo also has used AI to help develop predictive typing tech, with the aim of making it easier for people with ALS and other motor-limiting diseases to find the right words when a traditional keyboard or voice-to-speech is no longer an option.
Researchers are working to integrate the predictive system along with the avatar and an eye-tracking keyboard, with the ultimate goal of letting people with conditions such as ALS be seen and heard in the digital space.
“I have no doubt this pioneering proof of concept will one day help shape even more staggering innovations,” Morgan said.
“Our foundation was built on the dream that technology, and AI especially, can break through severe disabilities and ensure a right to create, connect, and live life joyfully. We’re making that happen,” Morgan added.
For Taylor, the project is also about the end goal.
“The avatar is incredible, but what matters most to me is that this technology could help change the lives of many more people facing ALS or other diseases — a way of showing how bright the future can still be,&#8221; Taylor said.

Novel AI-powered platform aims to help ALS patients to communicate

A new Canadian initiative seeks to advance development of an artificial intelligence (AI) program aimed at helping healthcare professionals detect possible signs of <a href="https://alsnewstoday.com/what-is-als/">amyotrophic lateral sclerosis</a> (ALS) in the disease&#8217;s early stages.
The AI program is crafted to analyze de-identified electronic medical records (EMRs) and detect individuals who should be tested for ALS or referred to a specialty center. It employs a <a href="https://www.alsprogress.ca/als-emr-program.php">clinical algorithm</a> — called MNd-5 and using real-world data — that screens EMRs to help physicians spot patients for whom investigations for the neurodegenerative disorder may be appropriate.
The initiative, <a href="https://www.alsprogress.ca">Process for Progress in ALS: An EMR-Based Practice Initiative</a>, is a collaboration of <a href="https://www.mt-pharma-ca.com/">Mitsubishi Tanabe Pharma Canada</a> (MTP-CA) and a trio of experts. These scientists, all members of the steering committee, are Angela Genge, MD, executive director of the ALS Centre of Excellence at The Neuro, in Montreal; Amer A. Ghavanini, PhD, division head of neurology at Trillium Health Partners in Mississauga, Canada; and Amanda Fiander, a neurologist at Maritime Neurology, in Nova Scotia.
&#8220;Early diagnosis and treatment of ALS can improve outcomes, but the disease can be difficult to diagnose in its early stages. The more time that passes before diagnosis, the less opportunities exist for disease-management for someone living with ALS,&#8221; Genge, said in a <a href="https://www.newswire.ca/news-releases/canadian-developed-ai-technology-aims-to-support-early-detection-of-als-830241196.html">MTP-CA press release</a>.
&#8220;Process for Progress in ALS is a unique advancement in AI medical technology which can help HCPs [healthcare providers] identify patients who present multiple warning signs for ALS so they can receive expedited follow-ups, diagnoses, and treatment if needed,&#8221; Genge added.
[recommended-reading id=85337]
<h3>Better tech needed to correctly ID early signs of ALS</h3>
While early <a href="https://alsnewstoday.com/als-diagnosis/">diagnosis</a> and <a href="https://alsnewstoday.com/als-treatment/">treatment</a> can improve outcomes, making such a determination in ALS often is challenging because the early signs and <a href="https://alsnewstoday.com/symptoms-of-als/">symptoms</a> of the progressive disease can be subtle, and no test provides a definitive diagnosis.
In Canada, such diagnoses take an average of 21 months, and come at a time when most patients are already showing more <a href="https://alsnewstoday.com/stages-of-als/">severe signs of muscle weakness</a> affecting multiple regions of the body.
The new algorithm, developed with the steering committee and deployed using the software platform of Toronto, Canada-based Ensho Health, a digital healthcare company, is intended for use as a clinical-decision support tool.
It prioritizes patients suspected of having ALS for clinical review. It works <a href="https://www.alsprogress.ca/als-algorithm.php">by comparing characteristics</a> of their health presentations, along with <a href="https://alsnewstoday.com/als-diagnosis/#Diagnostic_tests">electromyography test results</a>, with a reference population in which ALS or a number of other conditions has been diagnosed or ruled out.
[quote=&#8221;center&#8221;]We know that time is of the essence for people living with ALS, and initiatives like Process for Progress in ALS are critical in helping to ensure a timely diagnosis for people impacted by this devastating disease.[/quote]
&#8220;As a participant in the Process for Progress in ALS initiative, I believe it is a significant step forward to assist in our ability to identify ALS symptoms in the early stages and confidently refer people for further testing or to an ALS centre,&#8221; said Hamza Jalal, neurologist at Oakville Valley Health and a program participant.
&#8220;By intervening in patients&#8217; journeys earlier in the course of their disease, we can provide access to multidisciplinary care, approved therapies or clinical trials that can slow the progression of the disease and enhance the quality of their lives,&#8221; Jalal added.
Through integrations with electronic medical record systems, including Accuro, Cerner, Epic, Indivicare, Mediquest, and OscarPro, the screening service is available to about 80% of community neurologists, according to MTP-CA.
&#8220;We know that time is of the essence for people living with ALS, and initiatives like Process for Progress in ALS are critical in helping to ensure a timely diagnosis for people impacted by this devastating disease,&#8221; said Andy Zylak, president of MTP-CA, adding, &#8220;We are proud to support the introduction of this important AI technology as part of our long-standing commitment to leading scientific innovation, collaborating with HCPs, and working tirelessly to meet the needs of the ALS community.&#8221;

Canadian initiative to advance AI tech to better diagnose ALS

With an aim to share expertise and diminish duplicative research and care efforts in <a href="https://alsnewstoday.com/what-is-als/">amyotrophic lateral sclerosis</a> (ALS), two nonprofits — <a href="https://www.everythingals.org/">EverythingALS</a> and <a href="https://www.wewillcureals.com/">CureALS</a> — are combining operations on the EverythingALS platform, with an emphasis on research.
The new single nonprofit also will tackle efforts to find a cure for the related neurodegenerative condition frontotemporal dementia (FTD).
“We firmly believe that the proliferation of non-profit organizations in this field leads to duplication of efforts, wasting precious time, money, and most importantly, lives,” Bill Nuti, CureALS’ founder and CEO and now chairman of the board of directors for Everything ALS, said in a <a href="https://www.businesswire.com/news/home/20230711610576/en/EverythingALS-and-CureALS-Join-Forces-to-Discover-a-Cure-for-ALS">joint press release</a>.
If everyone knew what everyone knows, we would be so much further along in our pursuit of a cure,” Nuti said.
The merger leverages the organizations&#8217; disease knowledge, resources, and strategic plans, and fortifies their commitment to patient care, research, public and private partnerships, data innovation, and the use of artificial intelligence (AI). The goal is to propel innovative, citizen-driven ALS research, the new partners said.
[recommended-reading id=83660]
<h3>More research needed to advance &#8216;archaic&#8217; treatment</h3>
Going into the merger, EverythingALS was awaiting the results of several ongoing ALS digital biomarker observational studies — including the <a href="https://alsnewstoday.com/news/speech-study-artificial-intelligence-ai-technology-als-biomarkers/">Speech study</a> and the <a href="https://alsnewstoday.com/news/trial-planned-digital-home-monitoring-als-progression/">Radcliff study</a>  — with support from open data sharing. Those findings are expected in six to 12 months.
“Today, ALS is diagnosed at the equivalent state of Stage 4 cancer, while our treatment measurements remain archaic,&#8221; said Indu Navar, EverythingALS’s founder and CEO.
&#8220;We must break down silos and foster collaboration to accelerate progress,” Navar added.
AI already has played a prominent role in each organization&#8217;s efforts in ALS and FTD —  and that will continue.
“Artificial intelligence is the most consequential technology development in history and is central to both organizations,” Nuti said, adding that “it will significantly contribute to our research and advancements in the field.”
Unified operations on the EverythingALS platform will be guided by the following priorities:
<ul>
<li>To fund and support curative research with an emphasis on regeneration and repair of neurons and axons, or nerve fibers, using AI and technology innovations.</li>
<li>To drive digital biomarker identification and innovation to improve early diagnoses, treatments, and data feedback for curative investigations.</li>
<li>To enhance data sourcing, acquisition, and innovation to improve analysis and technology utilization.</li>
<li>To educate, empower, and support ALS patients so they understand their treatment options and make informed decisions.</li>
</ul>
“These priorities encompass the important strategic themes for the combined entity,” Nuti said.
“They reflect our commitment to advancing research, improving diagnosis and therapies, leveraging data for analysis and technology integration, and ensuring comprehensive support for people living with ALS and FTD,” he said.
Each organization has actively been building an expansive global ecosystem of partners that include industry, academia, and government. Both also have worked toward more research sharing, which fosters collaboration, knowledge sharing, and resource pooling to maximize the impact of ALS research and investigations.
“CureALS is EverythingALS&#8217;s vehicle to focus on research to discover a cure, without overlap in approach,” Navar said, adding, “Our synergy is evident, and our powerful strategic alignment will propel us forward in our mission.”
[quote=&#8221;center&#8221;]CureALS is EverythingALS&#8217;s vehicle to focus on research to discover a cure, without overlap in approach.[/quote]
Since 2020, EverythingALS has sought to advance research, foster innovation, and support patients and families. The pioneering CureALS has worked to fund groundbreaking research and empower those with ALS.
“By combining our resources, expertise, and strategic plans, EverythingALS is poised to drive revolutionary advancements and positively impact the lives of patients and their families,” the release stated.

Merging as EverythingALS, 2 nonprofits seek to better treatment

A new technology powered by artificial intelligence (AI) may one day help doctors diagnose people in the early stages of <a href="https://alsnewstoday.com/what-is-als/">amyotrophic lateral sclerosis</a> (ALS), according to data from a clinical trial.
Developed by <a href="https://pisontechnology.com">Pison</a>, the technology was able to detect involuntary muscle twitches, or fasciculations, and changes in muscles&#8217; electrical activity that helps distinguish healthy people from people <a href="https://alsnewstoday.com/living-with-als/">with ALS</a>.
This means it could serve as a digital disease biomarker of ALS, helping patients start treatment earlier when it&#8217;s more effective at slowing disease progression. It could also let doctors monitor patients and see how well they&#8217;re responding to treatment.
“If these results are validated, then this will enable clinicians to detect motor neuron involvement noninvasively and track it over the course of disease and with treatment interventions,” Terry Heiman-Patterson, a professor of neurology and study lead investigator, said in a <a href="https://www.businesswire.com/news/home/20230418005133/en/Landmark-Study-Finds-Pison-AI-Technology-Can-Detect-Neurological-Disorder-in-ALS-Patients">Pison press release</a>.
[recommended-reading id=78444]
Muscle movement occurs when the brain sends electrical signals through specialized nerve cells called motor neurons. These signals can be measured via a technique known as electroneurography, which uses a biosensor, or a set of electrodes, in contact with the skin.
Pison developed a neural biosensor for the wrist that contains electrodes similar to those used in electroneurography, but allows for round-the-clock recording of electrical signals. Machine learning, a type of AI, then helps turn the recordings into information a computer can understand.
Because ALS damages motor neurons, electrical signals from the brain are weaker, which can help the algorithms distinguish ALS patients from healthy people, perhaps even before <a href="https://alsnewstoday.com/symptoms-of-als/">symptoms of ALS</a> manifest.
“This technique may enable earlier diagnosis of motor neuron damage in presymptomatic gene carriers, help to detect motor neuron involvement in other disorders and provide a system that can remotely monitor progression in ALS and help in patient-centric clinical trial design,” said Heiman-Patterson, also the director of the MDA/ALS Center of Hope at Temple University.
The company is working to incorporate the technology into wearable devices, such as fitness trackers and smartwatches, which could help doctors collect information about motor neuron health and monitor their patients remotely. Having this technology in wearable devices also could help monitor the general population and potentially diagnose motor neuron-related conditions well before symptoms are evident.
“We have begun licensing our neural biosensor for incorporation into popular wearables such as smartwatches and fitness trackers for passive health monitoring, which will ultimately have the ability to track ALS and other neurological disorders in the form of neural health apps and telehealth services,” said John Croteau, CEO of Pison.
“New and better ways to diagnose and monitor people with ALS are urgently needed,” said Kuldip Dave, senior vice president of research at the <a href="https://www.als.org">ALS Association</a>, which funded the study, along with the <a href="https://www.nsf.gov">National Science Foundation</a>. “We are proud to have supported the initial testing of this promising new technology. We look forward to seeing the results of future studies to confirm and validate these findings with larger groups of participants.&#8221;
The company has announced plans to conduct larger and longer studies to better understand how well the technology can diagnose and and monitor the progression of ALS and other neurodegenerative diseases, such as <a href="https://multiplesclerosisnewstoday.com/multiple-sclerosis-overview/">multiple sclerosis</a> and <a href="https://parkinsonsnewstoday.com/what-is-parkinsons-disease/">Parkinson’s disease</a>.

Pison’s AI-powered technology may help identify early ALS

Significant delays in the diagnosis of <a href="https://alsnewstoday.com/what-is-als/">amyotrophic lateral sclerosis</a> (ALS) were revealed by a new large-scale analysis of real-world patient records using artificial intelligence (AI).
In fact, the median time from the first symptom to an ALS diagnosis was 11 months for these patients.
Similar delays were seen regardless of the location of symptom onset — either the limbs or the bulbar region that&#8217;s involved in speech and swallowing. But researchers noted that having shortness of breath, called dyspnea, as the first reported symptom led to further delays in diagnosis and neurologist referral.
&#8220;Dyspnea was fairly common and when it was present, a longer delay until visiting the specialist (neurologist) and until diagnosis were observed,&#8221; the team wrote, adding, &#8220;We cannot exclude that this symptom, so common in other [diseases], could have gone unnoticed or could have been attributed to other causes when appearing in very early stages of the disease.&#8221;
The study, “<a href="https://www.nature.com/articles/s41598-023-27863-2">Symptoms timeline and outcomes in amyotrophic lateral sclerosis using artificial intelligence</a>,” was published in the journal <a href="https://www.nature.com/srep/">Scientific Reports</a>.
[recommended-reading id=79108]
<h3>Delayed diagnosis found for ALS patients in real world</h3>
Real-world data describing ALS clinical characteristics, disease management, outcomes, and treatment responses can be found in patient electronic health records, called EHRs for short.
In recent years, computer-based AI and machine learning tools have been applied to EHRs stored in patient registries to extract and analyze real-world clinical information on large numbers of patients. This strategy can be especially helpful for rare diseases such as ALS, according to researchers.
“From a clinical standpoint, diseases with low prevalence are best understood using population-based registries with available follow-up information across large numbers of patients,” the investigators wrote.
To that end, a team based at the University Hospital of Albacete, in Spain, applied AI tools to describe the clinical profile, symptom onset, diagnosis, and relevant outcomes of ALS patients in that country. They used EHR data held in the Spanish SESCAM Healthcare Network registry.
The AI tool — called natural language processing or NLP — enabled computers to understand written text in medical records, then extract the relevant information.
Over the five-year study period, 250 patients were diagnosed with ALS, of whom 61.6% were male. The patients had a mean age of 64.7.
Among them, 159 (64%) had spinal ALS, which first affects the limbs, and 91 (36%) had bulbar ALS, marked by initial symptoms of speaking and swallowing difficulties. The most common co-existing medical conditions were high blood pressure and an imbalance of blood fats.
Data spanning at least one year before the <a href="https://alsnewstoday.com/als-diagnosis/">ALS diagnosis</a> was available for 208 patients. The most visited healthcare services before diagnosis were primary care, for 88.4%, and treatment in an emergency room, for 38.4%. Neurology was the most visited specialist service (38.8%).
The most common symptom up until diagnosis was weakness, followed by shortness of breath, speaking difficulties, swallowing problems, and muscle twitches.
Overall, the median diagnostic delay, or the time from the onset of symptoms to an ALS diagnosis, was 11 months. Similar delays were seen in both spinal and bulbar ALS subgroups.
[quote align=&#8221;center&#8221;]Our results point to &#8230; an overall diagnostic delay of 11 months before the first mention of ALS in patients’ [health records].[/quote]
Additionally, data showed that people who experienced shortness of breath as their first symptom had longer diagnostic delays, of a median of 12 months. Likewise, with shortness of breath as the first symptom, there was a longer delay in neurologist referral and subsequent diagnosis.
&#8220;The patient journey seems to play a role in [diagnostic] delay, with early referral to a neurologist linked to shorter timing to diagnosis,&#8221; the researchers wrote, noting that &#8220;ALS patients are frequently referred to other hospital departments before the neurologist.&#8221;
Compared with the period prior to a diagnosis, there was a two-to-threefold increase in speech problems (15.6% vs. 31.2%), swallowing difficulties (14.0% vs. 34.0%), and muscle twitches (13.6% vs. 37.2%) at the time of diagnosis.
During the median follow-up of 25 months after diagnosis, 52% of participants underwent a feeding tube insertion, while 64% received non-invasive breathing support and 16.4% had a breathing tube insertion, known as a tracheostomy. These procedures all occurred more frequently in the bulbar ALS group.
A total of 87.6% of patients were treated with riluzole (sold as <a href="https://alsnewstoday.com/als-treatment/rilutek-riluzole/">Rilutek</a>, <a href="https://alsnewstoday.com/tiglutik-riluzole-oral-suspension/">Tiglutik</a>, and <a href="https://alsnewstoday.com/exservan-riluzole-oral-film/">Exservan</a>).
Over a median of 19 months from ALS diagnosis, 87 patients (34.8%) died. When tracheostomy also was considered as a mortality outcome, that number increased to 110 (44.0%). The likelihood of feeding tube insertion and needing non-invasive ventilation was significantly higher for those with bulbar ALS.
These findings “highlight the diagnostic delay in ALS and revealed differences in the clinical characteristics and occurrence of major disease-specific events across ALS subtypes,” the researchers wrote.
&#8220;Our results point to &#8230; an overall diagnostic delay of 11 months before the first mention of ALS in patients’ EHRs,&#8221; the team concluded.

Tag: artificial intelligence

Novel AI-powered platform aims to help ALS patients to communicate

Canadian initiative to advance AI tech to better diagnose ALS

Merging as EverythingALS, 2 nonprofits seek to better treatment

Pison’s AI-powered technology may help identify early ALS

Delayed diagnosis in ALS found in new AI analysis of patient records