Optimising deep learning models for ophthalmological disorder classification.

Fundus imaging, a technique for recording retinal structural components and anomalies, is essential for observing and identifying ophthalmological diseases. Disorders such as hypertension, glaucoma, and diabetic retinopathy are indicated by structural alterations in the optic disc, blood vessels, fovea, and macula. Patients frequently deal with various ophthalmological conditions in either one or both eyes.

A Methodological Framework for Descriptive Phenomenological Research.

Background: Descriptive phenomenological research is crucial in nursing for understanding individuals' experiences, perceptions, and relationships, which are essential for person-centered healthcare. However, a common critique is that researchers often use phenomenological methods without fully comprehending their historical and philosophical foundations. Existing literature highlights discrepancies in the application of phenomenological principles by nurse researchers, particularly in their presentation of philosophical underpinnings and methodological details.

Multimodal autism detection: Deep hybrid model with improved feature level fusion.

Objective: Social communication difficulties are a characteristic of autism spectrum disorder (ASD), a neurodevelopmental condition. The earlier method of diagnosing autism largely relied on error-prone behavioral observation of symptoms. More intelligence approaches are in progress to diagnose the disorder, which still demands improvement in prediction accuracy.

Training in Cultural Competence for Mental Health Care: A Mixed-Methods Study of Students, Faculty, and Practitioners from India and USA.

Although the need to train clinicians to provide effective mental health care to individuals from diverse backgrounds has been recognized worldwide, a bulk of what we know about training in cultural competence (CC) is based on research conducted in the United States. Research on CC in mental health training from different world populations is needed due to the context-dependent nature of CC. Focusing on India and USA, two diverse countries that provide complementary contexts to examine CC, we explored graduate students', practicing clinicians', and faculty members' perspectives regarding CC training they received/provided and future training needs using mixed-methods.

Self-Care, Burnout, and Compassion Fatigue in Oncology Professionals.

Context: With the rising number of cancer cases in India, the stress levels of the treating team have increased. It has affected their self-care and made them susceptible to problems like burnout and compassion fatigue that adversely affect the quality of patient care.

Aims: The aim of the study was to assess and compare the levels of burnout, compassion fatigue, and self-care in three groups of oncology professionals (clinical oncologists, nurses, and psychologists).