Abstract: A method for early diagnosis of keratoconus based on multi-modal data considers a mutual relationship between both eyes using four refractive maps for corneas of the both eyes and absolute corneal elevation data, and combines the deep convolutional network method, the traditional support vector machine (SVM) method in machine learning, and the elevation map enhancement method with adjustable best-fit-sphere (BFS) to identify sensitivity and specificity of a focus and balance the sensitivity and specificity. With multi-dimensional comprehensive judgment of a keratoconus morbidity with a patient as a unit, combined with binocular data including both manual selection features and deep network learning from big data, the diagnosis method has higher robustness and accuracy.
Type:
Grant
Filed:
August 5, 2021
Date of Patent:
August 8, 2023
Assignees:
SHANGHAI MEDIWORKS PRECISION INSTRUMENTS CO., LTD., EYE AND ENT HOSPITAL OF FUDAN UNIVERSITY
Abstract: A dual-vector system for expressing an OTOF protein includes two nucleotide sequences, where a first nucleotide sequence includes two ITR sequences and a gene expression cassette inserted between the ITR sequences; a second nucleotide sequence includes two ITR sequences and a gene expression cassette inserted between the ITR sequences; the gene expression cassette of the first nucleotide sequence includes a promoter, an N-terminal coding sequence of OTOF, an N-terminal coding sequence of intein, and a polyA; and the gene expression cassette of the second nucleotide sequence includes a promoter, a C-terminal coding sequence of Intein, a C-terminal coding sequence of OTOF, and a polyA. The present disclosure further provides an adeno-associated virus packaged by the vector. The vector and the virus can recover hearing of bilateral ears by a unilateral ear administration in the field of deafness gene therapy large gene dual-vector delivery.
Type:
Application
Filed:
February 14, 2023
Publication date:
August 3, 2023
Applicants:
EYE & ENT HOSPITAL OF FUDAN UNIVERSITY, SHANGHAI REFRESHGENE THERAPEUTICS CO., LTD.
Abstract: A method for early diagnosis of keratoconus based on multi-modal data considers a mutual relationship between both eyes using four refractive maps for corneas of the both eyes and absolute corneal elevation data, and combines the deep convolutional network method, the traditional support vector machine (SVM) method in machine learning, and the elevation map enhancement method with adjustable best-fit-sphere (BFS) to identify sensitivity and specificity of a focus and balance the sensitivity and specificity. With multi-dimensional comprehensive judgment of a keratoconus morbidity with a patient as a unit, combined with binocular data including both manual selection features and deep network learning from big data, the diagnosis method has higher robustness and accuracy.
Type:
Application
Filed:
August 5, 2021
Publication date:
June 22, 2023
Applicants:
SHANGHAI MEDIWORKS PRECISION INSTRUMENTS CO., LTD., EYE AND ENT HOSPITAL OF FUDAN UNIVERSITY
Abstract: Disclosed is a vertigo diagnosis and treatment system including a frame, a revolution device, a rotation device and a seat, the frame comprising a primary frame and a secondary frame arranged oppositely. The revolution device includes a power mechanism and a slewing frame. The slewing frame is arranged between the primary frame and the secondary frame. The primary frame and the secondary frame provide slewing support for the slewing frame. The rotation device includes a power mechanism and a seat rotating frame. The vertigo diagnosis and treatment system further includes a seat biasing mechanism. Under the combined action of the revolution device and the rotation device, the vertigo diagnosis and treatment system according to the present invention can realize three-dimensional free rotation and hovering in any position, thus achieving vertigo diagnosis and treatment.
Type:
Grant
Filed:
February 20, 2020
Date of Patent:
April 20, 2021
Assignees:
EYE & ENT HOSPITAL OF FUDAN UNIVERSITY, SHENZHEN SECOND PEOPLE'S HOSPITAL, SHANGHAI ZEHNIT MEDICAL TECHNOLOGY CO., LTD.