Medical Areas Research Articles

Patients’ preferences, feelings, and benefits on Music-Based Intervention: A Pilot Study in COVID-19 Hospitalization

Introduction: COVID-19 patients survive in isolation with stringent measures of infection containment, leading to anxiety, fear, stress, loneliness, and depression. Music is recognized as useful to promote multiple health outcomes, including anxiolytic effects, pain-relieving, and relaxing effects that favour well-being and social interaction in healthcare settings. Objective: This study aimed to determine the impact of a pre-recorded music-based intervention on the music perception in hospitalized COVID-19 patients. Music appreciation, evoked emotions, and self-reported effects were explored and compared before and after music-based intervention, also considering the gender of the patients. Methods: This prospective study consisted of a pre-recorded music-based intervention administered to 272 patients hospitalized for COVID-19 by piping the music into rooms of inpatient medical area. Pre-recorded musical pieces of were selected by a music therapist considering specific formal and parametric characteristics, with the purposes of distraction, entertainment, relaxation, and emotional support. The patients’ opinions were collected using an ad hoc self-report questionnaire and a short data survey that followed the Consolidated Framework for Implementation Research (CFIR) guidelines. Results: Music resulted to be the preferred entertainment activity during hospitalization by 84.6% of patients, with 96.6% of them expecting a positive effect and a very high grade of usefulness attributed to music before hospitalization and even higher afterwards. The music intervention significantly changed the patients’ perception of music from everyday life to hospitalization (p<0.0001). It proved successful in evoking pleasure and fun, which raised from 18.4% of everyday life to 41.1% during hospitalization. The usefulness of listening music to alleviate unpleasant feelings including anxiety, fear, loneliness, and low mood in COVID-19 disease, had a significant increase from 22.5% to 60.0% after the music intervention. Conclusion: Music-based intervention, directed according to reference frameworks, provides self-reported social and emotional support in hospitalized patients for COVID-19.

Increase of multidrug-resistant bacteria after the COVID-19 pandemic in a major teaching Hospital in Sicily (2018-2021)

IntroductionThe COVID-19 pandemic has further highlighted the continuing threat of antimicrobial resistance (AMR) to global health and economic development. In the last two decades, AMR has raised increasing concern, with an estimated 4.95 million deaths globally due to bacterial AMR in 2019 alone.The aim of this study was to analyse the impact of the pandemic on the spread of multidrug-resistant organisms (MDROs) using data from the Hospital “P. Giaccone” in Palermo, comparing pre-pandemic and pandemic periods. MethodsThis observational study involved adult patients who were discharged from the hospital between 01 January 2018 and 31 December 2021. Hospital Discharge Cards were linked with microbiological laboratory reports to assess MDRO isolations. SARS-CoV-2 positivity during hospitalisation was evaluated using the National Institute of Health surveillance system. ResultsA total of 58 427 hospitalisations were evaluated in this study. Half the patients were aged over 65 years (N=26 984) and most admissions were in the medical area (N=31 716). During the hospitalisation period, there were 2681 patients (5%) with MDROs isolations, and 946 patients (2%) were positive for SARS-CoV-2. Multivariable analyses showed that during 2020 and 2021, there was a significantly increased risk of isolation of Staphylococcus aureus, Acinetobacter baumannii, and Klebsiella pneumoniae. Age, weight of the Diagnosis-Related Group (DRG), wards with higher intensity of care, and length-of-stay were associated with a higher risk of MDRO isolation. ConclusionThis study provides new insights into the impact of the COVID-19 pandemic on MDRO isolation and has important implications for infection control and prevention efforts in healthcare facilities. Age, DRG-weight, and longer hospital stays further increased the risk of MDRO isolation. Thus, it is imperative to improve and follow hospital protocols to prevent healthcare-associated infections.

A Survey on Using Linguistic Markers for Diagnosing Neuropsychiatric Disorders with Artificial Intelligence

Neuropsychiatric disorders affect the lives of individuals from cognitive, emotional, and behavioral aspects, impact the quality of their lives, and even lead to death. Outside the medical area, these diseases have also started to be the subject of investigation in the field of Artificial Intelligence: especially Natural Language Processing (NLP) and Computer Vision. The usage of NLP techniques to understand medical symptoms eases the process of identifying and learning more about language-related aspects of neuropsychiatric conditions, leading to better diagnosis and treatment options. This survey shows the evolution of the detection of linguistic markers specific to a series of neuropsychiatric disorders and symptoms. For each disease or symptom, the article presents a medical description, specific linguistic markers, the results obtained using markers, and datasets. Furthermore, this paper offers a critical analysis of the work undertaken to date and suggests potential directions for future research in the field.

Population-Based Study of the Incidence and Mortality Rate of Acute Aortic Dissection.

Acute aortic dissection (AAD) has high morbidity and a high fatality rate for a cardiovascular disease. Recent studies suggested that the incidence of AAD is increasing. However, the actual incidence and mortality rates of AAD are not well known. This study investigated the current epidemiology of AAD within the Yatsushiro medical jurisdictional area. A population-based review of patients with AAD was performed in a geographically well-defined area. Data were collected retrospectively from January 2011 to December 2020 for a total of 196 patients with AAD (Stanford Type A, n=126 [64.3%]; Stanford Type B, n=70 [35.7%]). The mean patient age was 74.3 years, and 55.6% (109/196) were women. The crude and age-standardized incidence rates of AAD in our medical jurisdictional area were 13.6 and 11.4 per 100,000 inhabitants per year, respectively. The crude and age-standardized 30-day mortality rates of AAD were 4.9 and 4.0 per 100,000 inhabitants per year, respectively. There were upward tendencies for both the incidence and 30-day mortality rate of AAD with age, with both being significantly higher in patients aged ≥85 years (P<0.001). This population-based study detected a higher incidence of AAD than previous studies, but reported a lower incidence of AAD in men than in women. Increasing age was associated with an increased incidence and mortality rate of AAD.

The distribution structure of medical and care resources based on regional characteristics throughout Japan in 2020

BackgroundGiven Japan’s rapidly aging population, the Ministry of Health, Labour and Welfare's policy of reducing hospital beds and replacing medical care with nursing care requires the establishment of a coordinated system of medical and care services tailored to regional characteristics. To gain useful knowledge for the development of such a system, this study aimed to identify differences in the structure of the relationship between medical and care resources due to differences in regional characteristics.MethodsInitially, regional characteristics were used to group all 334 secondary medical areas (SMA) in Japan by principal component analysis. Subsequently, the related structure of the distribution of medical and care resources for each group were compared. For these comparisons, first, the related structure of the distribution of medical and care resources nationwide was modeled using structural equation modeling. Secondly, multigroup analysis was conducted to investigate differences among the models across groups.ResultsThe nationwide SMAs were grouped largely based on urbanicity and middle-density regionality. The groups with high urbanicity and high middle-density regionality consisted of SMAs with a high and medium population density. By contrast, the low middle-density regionality group consisted of SMAs containing large cities with a high population density and depopulated areas with a low population density. The model of the related structure of the distribution of medical and care resources differed among these groups. In the non-urbanicity and middle-density regionality groups, nursing care abundance tended to increase acute care abundance. In addition, in all groups, nursing care abundance tended to increase long-term hospitalization care abundance and clinic care abundance (with beds).ConclusionsThe key finding of this study was that the government’s objective of reducing hospital beds may not be achieved solely by expanding nursing homes. This is because many of the models did not show a tendency that higher nursing care abundance reduces the values of the factors which increase more hospital beds. This finding was particularly relevant in middle-density regionality groups. This finding suggests that the location of nursing homes should be monitored because of concerns about the oversupply of nursing homes and sprawl in those areas.

‘I don’t want to be a guinea pig’ - Swedish women’s experiences of breast abscess treatment

BackgroundIt is well known that breastfeeding plays an important role in the health of women and children. However, women are not always given optimal support and most do not reach their breastfeeding goals. About one in five, breastfeeding women report mastitis and a small proportion of these develop a breast abscess. Our aim was to describe the experiences of a group of Swedish breastfeeding women who developed a breast abscess.MethodsA qualitative cross-sectional study with 18 study participants was undertaken in Sweden in 2017–2018. Potential participants were identified through electronic medical records at a university hospital and invited to participate in audio-recorded telephone interviews. Women were between 2 and 24 months postpartum at the time of the interview, on average 8 months. We conducted a thematic analysis in six steps according to Braun and Clark.ResultsOur analysis identified two themes: 1) Seeking care and receiving treatment was long and unpleasant, and 2) Importance of adequate professional care. Women who experienced a breast abscess were uncertain about where to ask for professional help. They often had a long wait for the right time to undergo the unpleasant and painful procedure of draining their breast abscess. The women felt it was important to receive professional care with respectful communication, continuity of care, and to receive adequate information, but they did not always receive this level of care.ConclusionsWomen with puerperal breast abscesses often fall between medical specialty areas. No longer under the care of obstetricians and maternity services, their problem is too complicated for general practitioners or emergency departments, but not regarded as serious by breast surgeons. Healthcare professionals urgently need adequate training in order to deal with breastfeeding problems and be able to offer women-centred care.

Transcriptomic Analysis Reveals the Potential Mechanisms for Improving Carotenoid Production in Rhodosporidium toruloides Z11 under Light Stress.

Carotenoids, as a type of tetraterpene compound, have been widely used in food, medical, and health areas owing to their antioxidant, immune enhancement, and disease risk reduction effects. Rhodosporidium toruloides is a promising oleaginous red yeast that can industrially synthesize carotenoids. In this study, the effects of different light exposure times and intervals on carotenoid production by R. toruloides Z11 were first investigated. Results showed that a higher carotenoid content (1.29 mg/g) can be achieved when R. toruloides Z11 was exposed to light for 12 h per day, which was increased by 1.98 times compared with that of dark cultivation. Transcriptome profiling revealed that light stress could effectively promote the gene expression levels of GGPS1 and AL1 in the carotenoid biosynthesis pathway and phr in the DNA photolysis pathway of R. toruloides. This work will provide a molecular foundation to further improve the production efficiency of carotenoids by genetic engineering.

Multiprofessional Approach for Chronic Kidney Disease (CKD) Risk Reduction and Prophylaxis in the Kushiro Medical Area

Chronic kidney disease (CKD) is closely related to disorders of various organs of the body and is also a factor in increasing social security costs such as medical costs for dialysis. Multiprofessional public health associations in Kushiro City jointly manage CKD-targeted action as "Kushiro CKD network" composed of medical/dental physicians, nurses, nutritionists and pharmacists. Pharmacists have played a central role in affixing a CKD sticker to a patient's medicine notebook when the patient's estimated glomerular filtration rate (eGFR) <45 mL/min/1.73 m2, in order to highlight the risk of CKD for those patients and related medical staff. There are many drugs that require dose reduction considering for renal function, but we had found cases where renal function was not monitored and pharmaceutical dispensation adjusted before the CKD network started. Therefore, we took this opportunity to investigate the impact of CKD stickers on pharmacists' work. During the period from August 2018 to August 2021, about 3200 CKD stickers were affixed by pharmacists, and about 4500 cases of decreased renal function were detected at pharmacies. In addition, there were 334 cases in which renal function deterioration was identified by the CKD stickers and led to further inquiries, of which 265 cases, or about 80%, resulted in prescription changes. Based on these results, it is considered that CKD stickers are effective method for pharmacies understand renal function deterioration and conduct appropriate prescription reviews. Finally, and perhaps most importantly, the use of CKD stickers can help assure that patients with renal impairment care treated with appropriate medication doses.

Risk Assess: A Symptom-Based Disease Predictor

Abstract: As of late, the medical care area has seen extraordinary changes through the joining of state of data collection. This study presents "Risk Assess", an imaginative web application fastidiously created with Flask. “Risk Assess” fills in as a complete stage, working with patient vitals for generating risk assessments. This python-based web application uses different Machine Learning models such as Classification and Regression (CART), Linear Support Vector Machine (SVM), Gaussian Naïve Bayes (NB), K-Nearest Neighbor (KNN) to analyze and build a model to predict if the given set of symptoms leads to a particular disease. Outstandingly, “Risk Assess” soothes out Cancer, Diabetes, Heart –Disease, Kidney-Disease and LiverDisease based prediction upgrading comfort and functional productivity. Our undertaking highlights a solid login page empowering clients to make novel qualifications utilizing their email addresses. By requiring a username and secret key attached to their email, we focus on both security and client comfort. This research paper contains working engineering, plan standards, and execution complexities, featuring the pivotal job of Machine Learning. “Risk Assess” epitomizes utilization of Python-based advances and Machine Learning, exhibiting the potential for predictions based on symptoms through creative computerized arrangements

Rule-Based Text Classification of Dental Diagnosis.

Unstructured medical records boast an abundance of information that could greatly facilitate medical decision-making and improve patient care. With the development of Natural Language Processing (NLP) methodology, the free-text medical data starts to attract more and more research attention. Most existing studies try to leverage the power of such unstructured data using Machine Learning algorithms, which would usually require a relatively large training set, and high computational capacity. However, when faced with a smaller-scale project, opting for an alternative approach may be more effective and practical. This project proposes an efficient and light-weight rule-based approach to categorize dental diagnosis data. It not only fills the void of dental records in the medical free-text processing area, but also demonstrates that with expertly designed research structure and proper implementation, simple method could achieve our study goal very competently.

Rethinking the Healthcare Facilities: The Role of the Buffer Space.

A working group conducted a survey on the use of the principle of buffer space (BS), which in case of emergencies, could benefit healthcare settings. The aim of the preliminary investigation is to define new research lines in hospitals' functional design. The global experience of the COVID-19 pandemic highlighted challenges faced by hospitals when responding promptly to emergencies, including spatial reorganization and suspension of ordinary medical activities for ensuring adequate management of the emergency surge of patients. The group designed questionnaires to be administered to healthcare staff and healthcare designers aimed at understanding varied conceptions and features of BSs. Content across the two surveys overlapped significantly, allowing for direct comparisons of responses, while also including tailored questions in relation to the respective experience and skills of the two groups of respondents. 102 healthcare professionals and 56 designers took part to the survey. Analysis of the responses permitted for initial recommendations regarding BS typology including (a) proximity to the emergency department (ED), intensive care units (ICUs), and inpatient wards (IWs); (b) location within hospitals but separate from other medical areas; (c) need for independent access; (d) organizational and spatial features similar to ED, ICUs, and IWs; (e) existing as a fully flexible operational space; and (f) BS bed capacity to be approximately 12% of ED beds. Although the analysis is related to the Italian context, the expansion of this preliminary research to alternate healthcare facilities and geographic areas is necessary for reaching a wide consensus by different professionals on this field. It serves as a starting point for future investigations regarding the implementation of BS in hospital settings.

UMLS-Based Approach for Developing VoiS: Voice-Activated Conversational Agent for Self-Management of Multiple Chronic Conditions

This abstract proposes a system design for an ontology-based conversational agent (CA) for the self-management of chronic conditions. The proposed system plans to integrate the largest medical ontology, the Unified Medical Language System (UMLS) (Bodenreider, 2004), aiming to narrow the vocabulary gaps between health professionals and patients and to make the agent more responsive to the users.&#x0D; Recently, conversational agents (CAs) like ChatGPT, or computer dialog systems that simulate human-to-human communication in natural language, have risen and gained popularity in various health contexts (Bin Sawad et al., 2022; Montenegro et al., 2019) including self-management of chronic conditions (Griffin et al., 2020). Despite their potential, the currently available CAs are often criticized for lacking the capability to understand natural language inputs (Montenegro et al., 2019). This limitation can be highlighted in medical areas due to the known vocabulary gaps between health professionals and health consumers. The knowledge-grounded dialog flow for CAs presents the potential to lift this limitation, making CAs naturally converse with their users.&#x0D; In the proposed voice-activated self-monitoring support (VoiS) application, the research team plans to integrate the UMLS to make the agent better understand lay terms from patients and properly map those terms to medical concepts. This automated process is expected to improve the user experience in two folds: a) promote the quality of communication between the patients and health providers and b) make the VoiS app more responsive to user inputs, overcoming accepting only constrained user inputs (e.g., multiple choice of utterance).

Colloidal one-pot synthesis and characterization of Glycine capped Al(x) doped ZnS QDs for efficient UV light assisted photo-degradation of Stilbene 420 dye

In thisstudy, successful synthesis and characterization of undoped and Al-doped ZnS quantum dots (QDs) capped with bio-friendly glycine (ZnSAl/Gly) are described. The synthesis is accomplished through a one-pot colloidal co-precipitation process, followed by the characterization of QDs using various analytical techniques.X-ray diffraction (XRD) and high-resolution transmission electron microscopy (HR-TEM) showed the formation of cubic-faced ZnS QDs, with the crystal size decreasing as the amount of Al doping increased. A ZnS phase layer on the QDs surface was also demonstrated by Fourier-transform infrared spectroscopy (FTIR) measurements. Field emission scanning electron microscopy with energy dispersive X-ray spectroscopy (FESEM-EDS) analysis was employed to examine the stoichiometry and shape of the synthesized QDs. Thermogravimetric analysis (TGA) showed a remarkable stability of Al-doped ZnS QDs over an extended period, enhancing their potential for a variety of applications. Measurements of the absorption band edge in the UV–Visible range demonstrated that Al ions were successfully incorporated into the ZnS lattice, causing a substantial red shift. This change, which caused the energy band gap to rise from 3.2 eV (ZnS/Gly) to 4.42 eV (ZnSAl1%/Gly), was attributed to the size confinement effect. The degradation of the Stilbene-420 dye under UV irradiation served as a test for the photodegradation capability of the synthesized QDs. The photodegradation efficiency of Al doping ranged from 60 % to 92 %, showing the induction of a significant number of crystalline structures with rising Al concentration. The Al-doped ZnS/Gly QDs are highly catalytic and photoactive, and they show great promise in the field of photoluminescence, medical and biological areas. Their potential for use as effective catalysts in waste water treatment methods is also remarkable.

The Role of Self-Efficacy, Motivation, and Connectedness in Dropout Intention in a Sample of Italian College Students

Dropout is a critical concern in higher education, with a considerable number of students leaving within the first two years of university. Dropout affects students’ well-being and their academic and career prospects, and institutions’ retention and graduation rates. The aim of this study was to explore the mediating role of motivation and cognitive strategies for learning in the relationship among self-efficacy, connectedness, and university dropout intention. A total of 790 Italian college freshmen were involved in this study. The sample was recruited through a web survey consisting of the Academic Motivation Scale, Perceived School Self-Efficacy Scale, University Connectedness Scale, and Self-Regulated Knowledge Scale-University. The freshmen’s intentions to drop out were assessed with five questions. The average age of the freshmen was 20.9 years, most of them were female, and were attending a degree program in the medical area. The results show that self-efficacy is the most important predictor of dropout intentions, followed by university connectedness. Self-regulated knowledge has an important role in predicting dropout intention by acting as a mediator between self-efficacy and motivation.This study underlines the importance of investing in training and orientation interventions in order to develop the skills to face the university path, increasing self-efficacy, motivation, and consequently students’ well-being.

Integrating prior knowledge to build transformer models

The big Artificial General Intelligence models inspire hot topics currently. The black box problems of Artificial Intelligence (AI) models still exist and need to be solved urgently, especially in the medical area. Therefore, transparent and reliable AI models with small data are also urgently necessary. To build a trustable AI model with small data, we proposed a prior knowledge-integrated transformer model. We first acquired prior knowledge using Shapley Additive exPlanations from various pre-trained machine learning models. Then, we used the prior knowledge to construct the transformer models and compared our proposed models with the Feature Tokenization Transformer model and other classification models. We tested our proposed model on three open datasets and one non-open public dataset in Japan to confirm the feasibility of our proposed methodology. Our results certified that knowledge-integrated transformer models perform better (1%) than general transformer models. Meanwhile, our proposed methodology identified that the self-attention of factors in our proposed transformer models is nearly the same, which needs to be explored in future work. Moreover, our research inspires future endeavors in exploring transparent small AI models.

Risk Factors Contributing to Disparities in Medical Treatment and Lower Survival Rates among Patients with Non-Small Cell Lung Cancer Induced by Residential Areas.

Because of a lack of medical resources for cancer treatment, particularly in rural areas, there are disparities in receiving medical treatment between urban and rural area. This study examined the association between residential area or areal deprivation index (ADI) and lack of surgical treatment or chemotherapy in patients with non-small cell lung cancer (NSCLC) in rural area, Japan. We analyzed the Aomori population-based cancer registry data from 926 cancer patients with NSCLC diagnosed between January and December 2014. Multivariable logistic regression and Cox proportional hazards models were used to examine association of patients' residential area/ADI with either surgery/chemotherapy or survival time, respectively. The residential area was divided into six medical areas based on the location of specialist hospitals. The medical areas were defined by Aomori Prefecture. The residential area (medical area) was strongly associated with access to cancer treatment for patients with NSCLC and ultimately contributed to lower survival rates. There was no significant influence in the distance from home to hospital and areal deprivation. We identified the risk factors related to a lack of medical treatment and shorter survival in rural area, Japan.

Addressing bioprinting challenges in tissue engineering

This paper discusses the current challenges and potential solutions in the field of bioprinting tissues and organs. It highlights that most bioprinted tissues are small, composed of few cell types, lack vascular systems, and have limited functionality. This paper emphasizes the need to develop methods to obtain various functional cell types, create vascular systems for nutrient delivery, and enhance the size and capabilities of 3D-printed tissue structures. Additionally, it explores the advancements in nanorobots in the medical field, focusing on their unique properties and applications in various medical areas like cancer, cardiology, and neurology.

ChatGPT-3.5 passes Poland's medical final examination-Is it possible for ChatGPT to become a doctor in Poland?

ChatGPT is an advanced chatbot based on Large Language Model that has the ability to answer questions. Undoubtedly, ChatGPT is capable of transforming communication, education, and customer support; however, can it play the role of a doctor? In Poland, prior to obtaining a medical diploma, candidates must successfully pass the Medical Final Examination. The purpose of this research was to determine how well ChatGPT performed on the Polish Medical Final Examination, which passing is required to become a doctor in Poland (an exam is considered passed if at least 56% of the tasks are answered correctly). A total of 2138 categorized Medical Final Examination questions (from 11 examination sessions held between 2013-2015 and 2021-2023) were presented to ChatGPT-3.5 from 19 to 26 May 2023. For further analysis, the questions were divided into quintiles based on difficulty and duration, as well as question types (simple A-type or complex K-type). The answers provided by ChatGPT were compared to the official answer key, reviewed for any changes resulting from the advancement of medical knowledge. ChatGPT correctly answered 53.4%-64.9% of questions. In 8 out of 11 exam sessions, ChatGPT achieved the scores required to successfully pass the examination (60%). The correlation between the efficacy of artificial intelligence and the level of complexity, difficulty, and length of a question was found to be negative. AI outperformed humans in one category: psychiatry (77.18% vs. 70.25%, p = 0.081). The performance of artificial intelligence is deemed satisfactory; however, it is observed to be markedly inferior to that of human graduates in the majority of instances. Despite its potential utility in many medical areas, ChatGPT is constrained by its inherent limitations that prevent it from entirely supplanting human expertise and knowledge.

ENHANCING WEARABLE AND MEDICAL CONNECTIVITY: A NOVEL PRINTED TRIPLE-BAND METAMATERIAL ANTENNA FOR WBAN/MBAN APPLICATIONS

This paper presents a novel, compact, monopole apple-shaped, and triple-band metamaterial printed antenna for wireless body area network (WBAN) and medical body area network (MBAN) applications. The antenna is backed by a tri-band uniplanar compact electromagnetic bandgap (UC-EBG) structure that acts as a ground plane and incorporates metamaterial triangular complementary splitring resonators (TCSRRs). The proposed printed textile antenna operates at 2.45 GHz for wireless local area network (WLAN), 3.5 GHz for 5G new radio (NR), and 5.8 GHz for industrial, scientific, and medical bands. Implementing the UC-EBG structure resulted in a 99&amp;#37; decrease in the specific absorption rate (SAR) values over 1 g and 10 g of tissues and achieved gains of 5.45, 6.09, and 7.63 dBi at 2.45, 3.5, and 5.8 GHz, respectively. Due to its high performance, low SAR values, and compact size of 39 &amp;times; 39 &amp;times; 2.84 mm&lt;sup&gt;3&lt;/sup&gt; (0.41 &amp;lambda;&lt;sub&gt;g&lt;/sub&gt; &amp;times; 0.41 &amp;lambda;&lt;sub&gt;g&lt;/sub&gt; &amp;times; 0.029 &amp;lambda;&lt;sub&gt;g&lt;/sub&gt; ), the proposed antenna is an attractive candidate for wearable healthcare, fitness monitoring devices, and other WBAN/MBAN applications.

RESTORE VISION: Novel advanced and repurposed therapeutics for vision restoration in a group of severe rare ocular diseases – Short introductory talk

Rare Eye Diseases (REDs) collectively represent a major cause of visual impairment and blindness for children and young adults in Europe. But importantly, REDs also affect adults and the aging population. Defective wound healing at the cornea and ocular surface, excessive inflammation, nerve degeneration, stem cell dysfunction, and aberrant vessel ingrowth are the common denominators in many REDs, representing a critical medical problem and an area of unmet medical need. The onset and progression of many REDs are characterized by common pathophysiologic mechanisms. The goal of many research groups is to disrupt these aberrant mechanisms with the aim of making therapy more effective. Current management is often prohibitively expensive, has low efficacy and leads to debilitating side effects, pointing to a critical medical problem and area of unmet medical need.Here, we will briefly introduce the RESTORE VISION project, which has been recently funded by the European Commission and brings together actors from across the full value chain: 6 leading research institutions, 3 SMEs and a European patient organization. The project will take a ground‐breaking approach to improve eye health by verifying disease pathomechanisms, using cutting‐edge models for each rare disease to test novel and repurposed compounds and determine drug mechanisms of action, formulating compounds as safe eye drop suspensions or subconjunctival drugs, and performing several first‐in‐human trials of novel therapies.