-
公开(公告)号：US20230024661A1
公开(公告)日：2023-01-26
申请号：US17787991
申请日：2020-12-22
Applicant: Szegedi Tudományegyetem
Inventor： Zsolt Datki , János Kálmán , Magdolna Pákáski
Abstract: The invention relates to an aqueous solution of AuCl3×2H2O or HAuCl4×4H2O, ZnCl2 or ZnSO4, and AgNO3 having an Au3+ concentration of 0.8 mM-1.6 mM, a Zn2+ concentration of 15 μM-50 μM, and an Ag+ concentration of 5 μM-50 μM. The invention extends to a kit comprising a solution of the invention, a method of preparing said solution, and the use of a solution of the invention, a solution prepared by a method of the invention, or a kit of the invention in predicting and/or diagnosing and/or monitoring a neurocognitive disorder of the Alzheimer's disease spectrum. The invention extends to a method for predicting and/or diagnosing and/or monitoring a neurocognitive disorder of the Alzheimer's disease spectrum in a patient comprising contacting a tear sample from the patient normalised for protein concentration with a solution of the invention; applying an amount of the tear sample thus obtained to a surface; allowing the tear sample to dry; and drawing a conclusion based on the pattern of the thus obtained dried tear sample, whether the patient is at risk of or suffers from a neurocognitive disorder of the Alzheimer's disease spectrum.
-
公开(公告)号：US12161481B2
公开(公告)日：2024-12-10
申请号：US17415418
申请日：2019-12-16
Applicant: Szegedi Tudományegyetem
Inventor： Gábor Gosztolya , Ildikó Hoffmann , János Kálmán , Magdolna Pákáski , László Tóth , Veronika Vincze
Abstract: The invention is a method for automatic detection of neurocognitive impairment, comprising, generating, in a segmentation and labelling step (11), a labelled segment series (26) from a speech sample (22) using a speech recognition unit (24); and generating from the labelled segment series (26), in an acoustic parameter calculation step (12), acoustic parameters (30) characterizing the speech sample (22). The method is characterised by determining, in a probability analysis step (14), in a particular temporal division of the speech sample (22), respective probability values (38) corresponding to silent pauses, filled pauses and any types of pauses for respective temporal intervals thereof; calculating, in an additional parameter calculating step (15), a histogram by generating an additional histogram data set (42) from the determined probability values (38) by dividing a probability domain into subdomains and aggregating durations of the temporal intervals corresponding to the probability values falling into the respective subdomains; and generating, in an evaluation step (13), decision information (34) by feeding the acoustic parameters (30) and the additional histogram data set (42) into an evaluation unit (32), the evaluation unit (32) using a machine learning algorithm. The invention is furthermore data processing system, a computer program product and a computer-readable storage medium for carrying out the method.
