Oncology/Hematology

Utilizing patient data: A tutorial on predicting second cancer with machine learning models.

BACKGROUND: The article explores the potential risk of secondary cancer (SC) due to radiation therapy (RT) and highlights the necessity for new modeling techniques to mitigate this risk.

External validation of the SORG machine learning for 90-day and 1-year mortality in patients suffering from extremity metastatic disease in an European cohort of 174 patients.

Accurate survival prediction of patients with long-bone metastases is challenging, but important for optimizing treatment. The Skeletal Oncology Research Group (SORG) machine learning algorithm (MLA) has been previously developed and internally validated to predict 90-day and 1-year survival. External validation showed promise in the United States and Taiwan. To ensure global generalizability, the...

Large Language Models-Enabled Digital Twins for Precision Medicine in Rare Gynecological Tumors

Rare gynecological tumors (RGTs) present major clinical challenges due to their low incidence and heterogeneity. The lack of clear guidelines leads ...

Identification of A0 minimum ablative margins for colorectal liver metastases: multicentre, retrospective study using deformable CT registration and artificial intelligence-based autosegmentation.

BACKGROUND: Several ablation confirmation software methods for minimum ablative margin assessment have recently been developed to improve local outcom...

Coalitions of AI-based Methods Predict 15-Year Risks of Breast Cancer Metastasis Using Real-World Clinical Data with AUC up to 0.9

Breast cancer is one of the two cancers responsible for the most deaths in women, with about 42,000 deaths each year in the US. That there are over ...

Identification of Prognostic Biomarkers for Stage III Non-Small Cell Lung Carcinoma in Female Nonsmokers Using Machine Learning

Lung cancer remains a leading cause of cancer-related deaths globally, with non-small cell lung cancer (NSCLC) being the most common subtype. This s...

Deep Learning to Predict Late-Onset Breast Cancer Metastasis: the Single Hyperparameter Grid Search (SHGS) Strategy for Meta Tuning Concerning Deep Feed-forward Neural Network

While machine learning has advanced in medicine, its widespread use in clinical applications, especially in predicting breast cancer metastasis, is ...

[A lightweight recurrence prediction model for high grade serous ovarian cancer based on hierarchical transformer fusion metadata].

High-grade serous ovarian cancer has a high degree of malignancy, and at detection, it is prone to infiltration of surrounding soft tissues, as well a...

[Research progress on colorectal cancer identification based on convolutional neural network].

Colorectal cancer (CRC) is a common malignant tumor that seriously threatens human health. CRC presents a formidable challenge in terms of accurate id...

Interpretable breast cancer classification using CNNs on mammographic images

Deep learning models have achieved promising results in breast cancer classification, yet their 'black-box' nature raises interpretability concerns....

Personalised Medicine: Establishing predictive machine learning models for drug responses in patient derived cell culture

The concept of personalised medicine in cancer therapy is becoming increasingly important. There already exist drugs administered specifically for p...

Patient-led skin cancer teledermatology without dermoscopy during the COVID-19 pandemic: important lessons for the development of future patient-facing teledermatology and artificial intelligence-assisted -self-diagnosis.

MySkinSelfie is a mobile phone application for skin self-monitoring, enabling secure sharing of patient-captured images with healthcare providers. Thi...

From Data Mining of Public Sources to Clinical Decision Support in Personalized Medicine.

Personalized medicine enables precise tumor treatment for a patient's molecular genetic profile. To devise optimal targeted treatment plans for patien...

Precise Identification of Oral Cancer Lesions Using Artificial Intelligence.

Dentists, especially those who are not oral lesion specialists and live in rural areas, need an artificial intelligence (AI) system for accurately ass...

Assessing the Performance of Deep Learning for Automated Gleason Grading in Prostate Cancer.

Prostate cancer is a dominant health concern calling for advanced diagnostic tools. Utilizing digital pathology and artificial intelligence, this stud...

A Greek Conversational Agent for Hematologic Malignancies: Usability and User Experience Assessment.

Enabling patients to actively document their health information significantly improves understanding of how therapies work, disease progression, and o...

Automatic Tumor Cellularity Measurement: AI-Based Pipeline for Multi-Organ Pathology Imaging.

Tumor Cellularity (TC) is an important metric for assessing organ tumor burden. However, manual cell counting is not feasible due to large volumes of ...

Beyond Tokens: Fair Evaluation of French Large Language Models for Clinical Named Entity Recognition.

Named Entity Recognition (NER) models based on Transformers have gained prominence for their impressive performance in various languages and domains. ...

Improving the Quality of Unstructured Cancer Data Using Large Language Models: A German Oncological Case Study.

With cancer being a leading cause of death globally, epidemiological and clinical cancer registration is paramount for enhancing oncological care and ...

Visualizing Future Breast Cancer Prognosis by Generative AI.

In Sweden, 30 percent of breast cancer cases are detected between screenings, leading to later staged cancer diagnoses. Aileen Health is preventing la...