A significant advancement in medical technology has emerged with the development of a new automated consciousness tool, designed to refine the diagnosis and improve recovery predictions for patients suffering from disorders of consciousness (DOC). Published by NR Times on January 12, 2026, the tool integrates six distinct assessment techniques: high-density electroencephalography (EEG), structural and functional Magnetic Resonance Imaging (MRI), diffusion MRI, and Positron Emission Tomography (PET). This innovative system was developed through research coordinated by Jacobo Sitt at the Paris Brain Institute and was rigorously tested in three major European centers across France, Germany, and Italy. The primary goal of the tool is to enable clinicians to provide more precise and individualized assessments for patients who have sustained severe brain damage following events such as stroke, traumatic brain injury, or cardiac arrest. Many of these patients exist in a state between wakefulness and complete unresponsiveness, making accurate diagnosis and prognosis particularly challenging. The research underscores that combining data from multiple neuroimaging modalities significantly enhances the model's performance, leading to more reliable predictions. Importantly, the study also revealed that the tests most effective for diagnosing the presence of consciousness are not necessarily the same ones that best predict a patient's long-term recovery trajectory. This multimodal approach addresses a critical gap in current clinical practice, where traditional behavioral scales can often miss signs of 'covert consciousness' in a substantial portion of unresponsive patients. The development of such advanced tools is globally relevant, including for countries like India, where preliminary surveys have indicated a low rate of using comprehensive assessment scales for DOC patients and a lack of adequate support services for caregivers.