4 citations · 7 across the 8 of their papers we have counts for
8 papers
Cognitive bias in LLM reasoning compromises interpretation of clinical oncology notes
Matthew W. Kenaston, Umair Ayub, Mihir Parmar +14
Despite high performance on clinical benchmarks, large language models may reach correct conclusions through faulty reasoning, a failure mode with safety implications for oncology…
MIRIAD: Augmenting LLMs with millions of medical query-response pairs
Qinyue Zheng, Salman Abdullah, Sam Rawal +7
LLMs are bound to transform healthcare with advanced decision support and flexible chat assistants. However, LLMs are prone to generate inaccurate medical content. To ground LLMs i…
Tensor Decomposition of Large-scale Clinical EEGs Reveals Interpretable Patterns of Brain Physiology
Teja Gupta, Neeraj Wagh, Samarth Rawal +3
Identifying abnormal patterns in electroencephalography (EEG) remains the cornerstone of diagnosing several neurological diseases. The current clinical EEG review process relies he…
Evaluating Latent Space Robustness and Uncertainty of EEG-ML Models under Realistic Distribution Shifts
Neeraj Wagh, Jionghao Wei, Samarth Rawal +2
The recent availability of large datasets in bio-medicine has inspired the development of representation learning methods for multiple healthcare applications. Despite advances in…
SCORE-IT: A Machine Learning-based Tool for Automatic Standardization of EEG Reports
Samarth Rawal, Yogatheesan Varatharajah
Machine learning (ML)-based analysis of electroencephalograms (EEGs) is playing an important role in advancing neurological care. However, the difficulties in automatically extract…
Multi-Perspective Semantic Information Retrieval
Samarth Rawal, Chitta Baral
Information Retrieval (IR) is the task of obtaining pieces of data (such as documents or snippets of text) that are relevant to a particular query or need from a large repository o…