Recent Articles





Computer-aided detection and diagnosis (CAD) systems can enhance the objectivity of visual inspection with acetic acid (VIA), which is widely used in low- and middle-income countries (LMICs) for cervical cancer detection. VIA’s reliance on subjective health care provider (HCP) interpretation introduces variability in diagnostic accuracy. CAD tools can address some limitations; nonetheless, understanding the contextual factors affecting CAD integration is essential for effective adoption and sustained use, particularly in resource-constrained settings.

Patients with melanoma receiving immunotherapy with immune-checkpoint inhibitors (ICIs) often experience immune-related adverse events (AEs), cancer-related fatigue and emotional distress, affecting health-related quality of life (HRQoL) and clinical outcome to immunotherapy. EHealth tools can aid cancer patients in addressing issues such as AEs and psychosocial well-being from various perspectives.

Esophageal and gastric cancer were among the top 10 most common cancers worldwide. And sex-specific differences were observed in the incidence. Due to their anatomic proximity, the two cancers have both different but also shared risk factors and epidemiological features. Exploring the potential correlated incidence pattern of them, holds significant importance in providing clues in the etiology and preventive strategies.

Skin cancers, including melanoma and keratinocyte cancers, are among the most common cancers worldwide, and their incidence is rising in most populations. Earlier detection of skin cancer leads to better outcomes for patients. Artificial intelligence (AI) technologies have been applied to skin cancer diagnosis, but many technologies lack clinical evidence and/or the appropriate regulatory approvals. There are few qualitative studies examining the views of relevant stakeholders or evidence about the implementation and positioning of AI technologies in the skin cancer diagnostic pathway.

Early-stage breast cancer has the complex challenge of carrying a favorable prognosis with multiple treatment options, including breast conserving surgery (BCS) or mastectomy. Social media is increasingly used as a source of information and as a decision tool for patients, and awareness of these conversations is important for patient counseling.

The rising number of cancer survivors and the shortage of healthcare professionals challenge the accessibility of cancer care. Health technologies are necessary for sustaining optimal patient journeys. To understand individuals' daily life during their patient journey, qualitative studies are crucial. However, not all patients wish to share their story with researchers

In medicine, the application of natural language processing (NLP) to tasks, such as information extraction and classification, has increased significantly. NLP plays a crucial role in structuring free-form radiology reports, facilitating the interpretation of textual content, and enhancing data utility through clustering techniques. Clustering allows for the identification of similar lesions and disease patterns across a broad dataset, making it useful for aggregating information and discovering new insights in medical imaging. However, most publicly available medical datasets are in English, with limited availability in other languages. This scarcity of datasets poses a challenge for developing models geared towards non-English downstream tasks.
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