AIMC Topic: Medical Oncology

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Integrating Artificial Intelligence-Driven Wearable Technology in Oncology Decision-Making: A Narrative Review.

Oncology
BACKGROUND: Clinical decision-making in oncology is a complex process influenced by numerous disease-related factors, patient demographics, and logistical considerations. With the advent of artificial intelligence (AI), precision medicine is undergoi...

Assessing the response quality and readability of chatbots in cardiovascular health, oncology, and psoriasis: A comparative study.

International journal of medical informatics
BACKGROUND: Chatbots using the Large Language Model (LLM) generate human responses to questions from all categories. Due to staff shortages in healthcare systems, patients waiting for an appointment increasingly use chatbots to get information about ...

Machine Learning-Assisted Decision Making in Orthopaedic Oncology.

JBJS reviews
ยป Artificial intelligence is an umbrella term for computational calculations that are designed to mimic human intelligence and problem-solving capabilities, although in the future, this may become an incomplete definition. Machine learning (ML) encom...

Artificial intelligence innovations in neurosurgical oncology: a narrative review.

Journal of neuro-oncology
PURPOSE: Artificial Intelligence (AI) has become increasingly integrated clinically within neurosurgical oncology. This report reviews the cutting-edge technologies impacting tumor treatment and outcomes.

Making sense of artificial intelligence and large language models-including ChatGPT-in pediatric hematology/oncology.

Pediatric blood & cancer
ChatGPT and other artificial intelligence (AI) systems have captivated the attention of healthcare providers and researchers for their potential to improve care processes and outcomes. While these technologies hold promise to automate processes, incr...

Artificial INtelligence to Support Informed DEcision-making (INSIDE) for Improved Literature Analysis in Oncology.

European urology focus
BACKGROUND: Defining optimal therapeutic sequencing strategies in prostate cancer (PC) is challenging and may be assisted by artificial intelligence (AI)-based tools for an analysis of the medical literature.

Towards equitable AI in oncology.

Nature reviews. Clinical oncology
Artificial intelligence (AI) stands at the threshold of revolutionizing clinical oncology, with considerable potential to improve early cancer detection and risk assessment, and to enable more accurate personalized treatment recommendations. However,...

Towards proactive palliative care in oncology: developing an explainable EHR-based machine learning model for mortality risk prediction.

BMC palliative care
BACKGROUND: Ex-ante identification of the last year in life facilitates a proactive palliative approach. Machine learning models trained on electronic health records (EHR) demonstrate promising performance in cancer prognostication. However, gaps in ...

Role of artificial intelligence in brain tumour imaging.

European journal of radiology
Artificial intelligence (AI) is a rapidly evolving field with many neuro-oncology applications. In this review, we discuss how AI can assist in brain tumour imaging, focusing on machine learning (ML) and deep learning (DL) techniques. We describe how...