An interpretable artificial intelligence model based on CT for prognosis of intracerebral hemorrhage: a multicenter study.

Objectives: To develop and validate a novel interpretable artificial intelligence (AI) model that integrates radiomic features, deep learning features, and imaging features at multiple semantic levels to predict the prognosis of intracerebral hemorrhage (ICH) patients at 6 months post-onset.

Materials And Methods: Retrospectively enrolled 222 patients with ICH for Non-contrast Computed Tomography (NCCT) images and clinical data, who were divided into a training cohort (n = 186, medical center 1) and an external testing cohort (n = 36, medical center 2). Following image preprocessing, the entire hematoma region was segmented by two radiologists as the volume of interest (VOI).

Predicting Outcome of Patients With Cerebral Hemorrhage Using a Computed Tomography-Based Interpretable Radiomics Model: A Multicenter Study.

Objective: The aim of this study was to develop and validate an interpretable and highly generalizable multimodal radiomics model for predicting the prognosis of patients with cerebral hemorrhage.

Methods: This retrospective study involved 237 patients with cerebral hemorrhage from 3 medical centers, of which a training cohort of 186 patients (medical center 1) was selected and 51 patients from medical center 2 and medical center 3 were used as an external testing cohort. A total of 1762 radiomics features were extracted from nonenhanced computed tomography using Pyradiomics, and the relevant macroscopic imaging features and clinical factors were evaluated by 2 experienced radiologists.

A pedigree with retinitis pigmentosa and its concomitant ophthalmic diseases.

Aim: To characterize the ophthalmic clinical phenotype of a family with retinitis pigmentosa (RP) and closed-angle glaucoma and to detect pathogenic genes and mutation sites causing RP in this family.

Methods: Ophthalmic clinic performance was examined in detail in 8 enrolled family members. Genomic DNA was extracted from the peripheral blood of 4 family members for whole-exome sequencing (WES) to select potential genetic mutations whose structures were identified by bioinformatics analysis.

Magnetic resonance imaging assessment of the lateral geniculate nucleus volume and height in patients with glaucoma: a Meta-analysis.

Aim: To evaluate the lateral geniculate nucleus (LGN) volume and height using magnetic resonance imaging (MRI) in glaucoma patients.

Methods: Literatures retrieval was carried out through PubMed, Web of Science, Embase, and Cochrane Library. Studies that compared the volume and height of LGN in glaucoma patients with that in control subjects were included.

Antioxidative and Mitochondrial Protection in Retinal Pigment Epithelium: New Light Source in Action.

Low-color-temperature light-emitting diodes (LEDs) (called 1900 K LEDs for short) have the potential to become a healthy light source due to their blue-free property. Our previous research demonstrated that these LEDs posed no harm to retinal cells and even protected the ocular surface. Treatment targeting the retinal pigment epithelium (RPE) is a promising direction for age-related macular degeneration (AMD).

[Application of FTIR spectrometry to monitoring chemosensitivity of breast cancer cell line using 5-FU].

The purpose of the present study was to compare the changes of infrared spectrum of breast cancer cell line MCF-7 treated by 5-fluorouracil with various concentrations and treating time. The results indicate that the relative intensity ratios of I2 920/I1 460 increased in the FTIR spectra of cell line MCF-7 while I1 400/I1 460, I1 080 /I1 550 and I1 240/I1 550 decreased significantly within forty-eight hours, however, no regular change was observed during 48-72 hours. The relative intensity ratio of I1 640/ I1 550 decreases along with the increase in the concentration of 5-fluorouracil.