Differences in technical and clinical perspectives on AI validation in cancer imaging: mind the gap!

Good practices in artificial intelligence (AI) model validation are key for achieving trustworthy AI. Within the cancer imaging domain, attracting the attention of clinical and technical AI enthusiasts, this work discusses current gaps in AI validation strategies, examining existing practices that are common or variable across technical groups (TGs) and clinical groups (CGs). The work is based on a set of structured questions encompassing several AI validation topics, addressed to professionals working in AI for medical imaging.

Artificial Intelligence for Optimizing Cancer Imaging: User Experience Study.

Background: The need for increased clinical efficacy and efficiency has been the main force in developing artificial intelligence (AI) tools in medical imaging. The INCISIVE project is a European Union-funded initiative aiming to revolutionize cancer imaging methods using AI technology. It seeks to address limitations in imaging techniques by developing an AI-based toolbox that improves accuracy, specificity, sensitivity, interpretability, and cost-effectiveness.

Neuropalliative Care Needs Checklist for Motor Neuron Disease and Parkinson's Disease: A Biopsychosocial Approach.

Objectives: Neurodegenerative disorders necessitate comprehensive palliative care due to their progressive and irreversible nature. Limited studies have explored the comprehensive assessment needs of this population. This present study is designed to develop a checklist for evaluating the palliative care needs of individuals with motor neuron disease (MND) and Parkinson's disease (PD).

Cancer care pathways across seven countries in Europe: What are the current obstacles? And how can artificial intelligence help?

Background: Cancer poses significant challenges for healthcare professionals across the disease pathway including cancer imaging. This study constitutes part of the user requirement definition of INCISIVE EU project. The project has been designed to explore the full potential of artificial intelligence (AI)-based technologies in cancer imaging to streamline diagnosis and management.

Palliative Care Needs and Care Giver Burden in Neurodegenerative Diseases: A Cross Sectional Study.

Background And Aims: Palliative care is an important area of intervention in neurodegenerative diseases. The aim of this study is to understand the relationship between Palliative Care Needs and Caregiver Burden among persons diagnosed with neurodegenerative diseases.

Methods: A cross-sectional study design was adopted to explore the research problem.

Palliative Care Social Work In India: Current Status and Future Directions.

Palliative care (PC) involves total care for persons suffering from life-threatening illnesses and their families. Social work as a profession and an academic discipline is gaining momentum in India for the past few decades. A large number of professional social workers are working with individuals, families, and communities to provide PC in India.