Image by David Whelan, from Wikimedia
North Korea Hackers Target Global Industries in Cyber Espionage Campaign
- Written by Kiara Fabbri Former Tech News Writer
- Fact-Checked by Justyn Newman Former Lead Cybersecurity Editor
The FBI and other cybersecurity organisations released a Cybersecurity Advisory , highlighting these espionage activities. The cyber actors have primarily targeted defence, aerospace, nuclear, and engineering entities worldwide. Their objective is to steal sensitive and classified technical information and intellectual property to advance the DPRK’s military and nuclear programs.
The authors of the Cybersecurity Advisory warn that the group continue to threaten various industry sectors globally, including entities in the U.S., UK, South Korea, Japan, and India. The RGB’s 3rd Bureau finances its espionage activities through ransomware attacks on U.S. healthcare organisations.
As the cyber threat landscape continues to evolve, international cooperation will be crucial in combating these sophisticated adversaries.
Image from Uplash+
AI Shows Promise in Tracking Parkinson’s Disease Progression
- Written by Kiara Fabbri Former Tech News Writer
- Fact-Checked by Justyn Newman Former Lead Cybersecurity Editor
A study published on July 23 explores how artificial intelligence (AI) could revolutionise the diagnosis of Parkinson’s disease. This new method could offer hope for improved patient care and treatment. Developed by researchers at the University of Florida, the technology analyses video recordings of patients performing simple tasks to detect subtle changes in movement associated with the disease.
Parkinson’s disease is a brain disorder affecting movement. Symptoms worsen over time, and diagnosis relies on a series of exercises and maneuvers performed by the patient. The commonly used Movement Disorder Society-Unified Parkinson’s Disease Rating Scale ( MDS-UPDRS ) tracks disease progression. However, this scale is limited in its ability to capture subtle changes and can be subjective. The AI system offers a more objective and detailed approach.
Participants were instructed to perform a standardized finger-tapping task while seated in front of a video camera . A clinician was present to guide the task and provide a clinical rating. The recorded videos were then processed using AI algorithms to assess Parkinson’s disease symptom progression.
“By studying these videos, we could detect even the smallest alterations in hand movements that are characteristic of Parkinson’s disease but might be difficult for clinicians to visually identify,” said Diego Guarin , the study’s lead researcher. “The beauty of this technology is that a patient can record themselves performing the test, and the software analyzes it and informs the clinician how the patient is moving so the clinician can make decisions.”
Guarin claims that this automated system also revealed previously unnoticed movement details, such as the speed at which a patient opens or closes their finger, and how movement properties change with each tap.
In his statement, Guarin affirms, “We’ve seen that, with Parkinson’s disease, the opening movement is delayed, compared to the same movement in individuals that are healthy […] This is new information that is almost impossible to measure without the video and computer, telling us the technology can help to better characterize how Parkinson’s disease affects movement and provide new markers to help evaluate the effectiveness of therapies.”
While promising, the study acknowledges some limitations. These include reliance on single-rater assessments, and exclusion of patients with very mild or severe symptoms. Future research is needed to validate the findings in a larger and more diverse patient population.
Overall, the results suggest that video-based assessments could significantly improve the diagnosis, monitoring, and treatment of Parkinson’s disease. The researchers aim in future work to test this strategy with home-recorded videos without clinician guidance.
These findings, together with a recent Alzheimer’s research demonstrates AI’s potential to predict disease progression, underscoring the transformative role of AI for neurodegenerative diseases.
