Evaluating the feasibility of using Generative Models to generate Chest X-Ray Data

In this paper, we explore the feasibility of using generative models, specifically Progressive Growing GANs (PG-GANs) and Stable Diffusion fine-tuning, to generate synthetic chest X-ray images for medical diagnosis purposes. Due to ethical concerns, obtaining sufficient medical data for machine learning is a challenge, which our approach aims to address by synthesising more data. We utilised the Chest X-ray 14 dataset for our experiments and evaluated the performance of our models through qualitative and quantitative analysis. Our results show that the generated images are visually convincing and can be used to improve the accuracy of classification models. However, further work is needed to address issues such as overfitting and the limited availability of real data for training and testing. The potential of our approach to contribute to more effective medical diagnosis through deep learning is promising, and we believe that continued advancements in image generation technology will lead to even more promising results in the future

EKSPERCKIE SYSTEMY ROZMYTE DO OCENY INTENSYWNOŚCI REAKTYWNEGO OBRZĘKU TKANEK MIĘKKICH U PACJENTÓW Z CUKRZYCĄ

The paper analyzes the main areas of application of mathematical methods in medical diagnostics, formulates principles of diagnostics based on fuzzy logic; developed mathematical models and algorithms that formalize the process of making diagnostic decisions based on fuzzy logic with quantitative and qualitative parameters of the patient's condition; developed mathematical models of membership function. Mathematical models and algorithms have been developed that formalize the process of making diagnostic decisions based on fuzzy logic with quantitative and qualitative parameters of the patient's condition; developed mathematical models of membership functions, formalizing the representation of quantitative and qualitative parameters of the patient's condition in the form of fuzzy sets, used in models and algorithms for diagnosis and finding a diagnosis of assessing the intensity of reactive postoperative edema in patients of all study groups. An expert system was implemented for solving the problems of medical diagnosis based on fuzzy logic when assessing the intensity of reactive swelling of soft tissues, which develops in the postoperative period in patients of all study groups against the background of diabetes. The paper analyzes the main areas of application of mathematical methods in medical diagnostics, formulates the principles of diagnostics based on fuzzy logic.W pracy analizowane są główne kierunki zastosowania metod matematycznych w diagnostyce medycznej, formułowane są zasady diagnostyki opartej na logice rozmytej; opracowywane są modele matematyczne i algorytmy formalizujące proces podejmowania decyzji diagnostycznych w oparciu o logikę rozmytą z ilościowymi i jakościowymi parametrami stanu pacjenta; opracowywane są modele matematyczne funkcji przynależności. Opracowano modele matematyczne i algorytmy formalizujące proces podejmowania decyzji diagnostycznych w oparciu o logikę rozmytą z ilościowymi i jakościowymi parametrami stanu pacjenta; opracowano modele matematyczne funkcji przynależności formalizujące reprezentację ilościowych i jakościowych parametrów stanu pacjenta w postaci zbiorów rozmytych wykorzystywanych w modelach i algorytmach diagnozowania i znajdowania rozpoznania nasilenia reaktywnego obrzęku pooperacyjnego u pacjentów wszystkich grup badawczych. Wdrożono system ekspercki do rozwiązywania problemów diagnostyki medycznej oparty na logice rozmytej w ocenie nasilenia reaktywnego obrzęku tkanek miękkich, który rozwija się w okresie pooperacyjnym u pacjentów wszystkich grup badawczych z cukrzycą. W artykule przeanalizowano cechy zastosowania metod matematycznych w diagnostyce medycznej, sformułowano zasady diagnostyki opartej na logice rozmytej

The problems of offenders with mental disorders: A plurality of perspectives within a single mental health care organisation

Managers, doctors, nurses, occupational therapists, social workers, psychologists, unqualified staff and service users were interviewed for a qualitative study of risk management and rehabilitation in an inner city medium secure forensic mental health care unit. Different professional orientations to service user problems were identified. Doctors focused primarily on the diagnosis of mental disorder, which they managed mainly through pharmaceutical interventions. Psychologists were principally concerned with personal factors, for example service user insight into their biographical history. Occupational therapists concentrated mainly on daily living skills, and social workers on post-discharge living arrangements. Some front line nurses, held accountable for security lapses, adopted a criminogenic approach. Service users were more likely than professionals to understand their needs in terms of their wider life circumstances. These differences are explored qualitatively in relation to four models of crossdisciplinary relationships: monoprofessional self-organisation combined with restricted communication; hermeneutic reaching out to other perspectives; the establishment of interdisciplinary sub-systems; and transdisciplinary merger. Relationships between professions working in this unit, as portrayed in qualitative interviews, corresponded mainly to the first model of monoprofessional self-organisation. Reasons for restricted crossdisciplinary understanding, particularly the wide power/status differences between the medical and other professions, and between staff and patients, are discussed

The problems of offenders with mental disorders: A plurality of perspectives within a single mental health care organisation

Managers, doctors, nurses, occupational therapists, social workers, psychologists, unqualified staff and service users were interviewed for a qualitative study of risk management and rehabilitation in an inner city medium secure forensic mental health care unit. Different professional orientations to service user problems were identified. Doctors focused primarily on the diagnosis of mental disorder, which they managed mainly through pharmaceutical interventions. Psychologists were principally concerned with personal factors, for example service user insight into their biographical history. Occupational therapists concentrated mainly on daily living skills, and social workers on post-discharge living arrangements. Some front line nurses, held accountable for security lapses, adopted a criminogenic approach. Service users were more likely than professionals to understand their needs in terms of their wider life circumstances. These differences are explored qualitatively in relation to four models of crossdisciplinary relationships: monoprofessional self-organisation combined with restricted communication; hermeneutic reaching out to other perspectives; the establishment of interdisciplinary sub-systems; and transdisciplinary merger. Relationships between professions working in this unit, as portrayed in qualitative interviews, corresponded mainly to the first model of monoprofessional self-organisation. Reasons for restricted crossdisciplinary understanding, particularly the wide power/status differences between the medical and other professions, and between staff and patients, are discussed

Exploration of Interpretability Techniques for Deep COVID-19 Classification using Chest X-ray Images

The outbreak of COVID-19 has shocked the entire world with its fairly rapid spread and has challenged different sectors. One of the most effective ways to limit its spread is the early and accurate diagnosis of infected patients. Medical imaging such as X-ray and Computed Tomography (CT) combined with the potential of Artificial Intelligence (AI) plays an essential role in supporting the medical staff in the diagnosis process. Thereby, the use of five different deep learning models (ResNet18, ResNet34, InceptionV3, InceptionResNetV2, and DenseNet161) and their Ensemble have been used in this paper, to classify COVID-19, pneumoni{\ae} and healthy subjects using Chest X-Ray. Multi-label classification was performed to predict multiple pathologies for each patient, if present. Foremost, the interpretability of each of the networks was thoroughly studied using techniques like occlusion, saliency, input X gradient, guided backpropagation, integrated gradients, and DeepLIFT. The mean Micro-F1 score of the models for COVID-19 classifications ranges from 0.66 to 0.875, and is 0.89 for the Ensemble of the network models. The qualitative results depicted the ResNets to be the most interpretable model

Predicting health-related quality of life in Spanish adolescents with allergic rhinoconjunctivitis and bronchial asthma

This study analyzed the predictive power of sociodemographic (age, sex) and medical variables (months since diagnosis and in treatment, immunotherapy, number of environmental allergens, food allergies or atopic dermatitistypes) on the quality of life of patients with rhinoconjunctivitis and bronchial asthma, using models based on comparative qualitative fuzzy analysis to compare them according to the pathology(s). Retrospective cross-sectional design.Sixty-four adolescents (65.60% boys) diagnosed with rhinoconjunctivitis and/or bronchial asthma aged between 12 and 16 years old (M= 14.02; SD = 1.45). The data were collected between February 2019 and January 2020 using the Brief Disease Perception Questionnaire (B-IPQ), the Adolescent Rhinoconjunctivitis Quality of Life Questionnaire (AdolRQoLQ) and the Respiratory Disease Questionnaire Self-administered and Standardized Chronicle (CRQSAS). Qualitative comparative analysis models (QCA) were used. In the QCA models, the various combinations indicated that the variables that predicted a higher quality of life for both rhinocojuntivitis symptoms and respiratory symptoms were receiving longerterm immunotherapy and a perceived lower threat of the disease. The consistencies of the models vary between 23-29%. In conclusion, the patients' QoL was explained by the presence of longerterm immunotherapy and a less threatening perception of the disease. Therefore, early multidisciplinary diagnosis and treatment is importan

Barriers and facilitators to GP-patient communication about emotional concerns in UK primary care: a systematic review.

Background In the UK, general practitioners (GPs) are the most commonly used providers of care for emotional concerns. Objective To update and synthesize literature on barriers and facilitators to GP–patient communication about emotional concerns in UK primary care. Design Systematic review and qualitative synthesis. Method We conducted a systematic search on MEDLINE (OvidSP), PsycInfo and EMBASE, supplemented by citation chasing. Eligible papers focused on how GPs and adult patients in the UK communicated about emotional concerns. Results were synthesized using thematic analysis. Results Across 30 studies involving 342 GPs and 720 patients, four themes relating to barriers were: (i) emotional concerns are difficult to disclose; (ii) tension between understanding emotional concerns as a medical condition or arising from social stressors; (iii) unspoken assumptions about agency resulting in too little or too much involvement in decisions and (iv) providing limited care driven by little time. Three facilitative themes were: (v) a human connection improves identification of emotional concerns and is therapeutic; (vi) exploring, explaining and negotiating a shared understanding or guiding patients towards new understandings and (vii) upfront information provision and involvement manages expectations about recovery and improves engagement in treatment. Conclusion The findings suggest that treatment guidelines should acknowledge: the therapeutic value of a positive GP–patient relationship; that diagnosis is a two-way negotiated process rather than an activity strictly in the doctor’s domain of expertise; and the value of exploring and shaping new understandings about patients’ emotional concerns and their management

A survey of statistics in three UK general practice journal

Background Many medical specialities have reviewed the statistical content of their journals. To our knowledge this has not been done in general practice. Given the main role of a general practitioner as a diagnostician we thought it would be of interest to see whether the statistical methods reported reflect the diagnostic process. Methods Hand search of three UK journals of general practice namely the British Medical Journal (general practice section), British Journal of General Practice and Family Practice over a one-year period (1 January to 31 December 2000). Results A wide variety of statistical techniques were used. The most common methods included t-tests and Chi-squared tests. There were few articles reporting likelihood ratios and other useful diagnostic methods. There was evidence that the journals with the more thorough statistical review process reported a more complex and wider variety of statistical techniques. Conclusions The BMJ had a wider range and greater diversity of statistical methods than the other two journals. However, in all three journals there was a dearth of papers reflecting the diagnostic process. Across all three journals there were relatively few papers describing randomised controlled trials thus recognising the difficulty of implementing this design in general practice

Insights into the impact of clinical encounters gained from personal accounts of living with advanced cancer.

Aim To describe the impact of interactions with health care professionals revealed by people’s accounts of living and dying with cancer; to explore reasons for the observed effects; and thus, to consider the implications for practice. Background The importance of practitioner–patient interactions is enshrined within professional values. However, our understanding of how and why the consultation impacts on outcomes remains underdeveloped. Stories recounted by people living and dying with cancer offer important insights into illness experience, including the impact of contact with health services, framed within the context of the wider social setting in which people live their lives. From our recent study of distress in primary palliative care patients, we describe how people’s accounts revealed both therapeutic and noxious effects of such encounters, and discuss reasons for the observed effects. Method A qualitative study with a purposive sample of 19 primary palliative care patients: (8 men, 11 at high risk of depression). In-depth interviews were analysed using the iterative thematic analysis described by Lieblich. Findings Living with cancer can be an exhausting process. Maintaining continuity of everyday life was the norm, and dependent on a dynamic process of balancing threats and supports to people’s emotional well-being. Interactions with health care professionals were therapeutic when they provided emotional, or narrative, support. Threats arose when the patient’s perception of the professional’s account of their illness experience was at odds with the person’s own sense of their core self and what was important to them. Our findings highlight the need for a framework in which clinicians may legitimately utilize different illness models to deliver a personalized, patient-centred assessment of need and care. The work provides testable hypotheses supporting development of understanding of therapeutic impact of the consultation