Zobrazeno 1 - 10
of 997
pro vyhledávání: '"P. Chitkara"'
Publikováno v:
Current Oncology, Vol 31, Iss 8, Pp 4338-4345 (2024)
Chimeric Antigen Receptor T-cell (CAR-T) therapy uses genetically engineered T-cells with specific binding sites. This therapy allows for tumor specificity and durable treatment responses for patients with hematological malignancies. In this review,
Externí odkaz:
https://doaj.org/article/e1b3a89939984ba5bd3fc892e6b4dbc2
Autor:
Klumpp, Philipp, Chitkara, Pooja, Sarı, Leda, Serai, Prashant, Wu, Jilong, Veliche, Irina-Elena, Huang, Rongqing, He, Qing
The awareness for biased ASR datasets or models has increased notably in recent years. Even for English, despite a vast amount of available training data, systems perform worse for non-native speakers. In this work, we improve an accent-conversion mo
Externí odkaz:
http://arxiv.org/abs/2303.00802
Advancements in technologies related to working with omics data require novel computation methods to fully leverage information and help develop a better understanding of human diseases. This paper studies the effects of introducing graph contrastive
Externí odkaz:
http://arxiv.org/abs/2301.02242
Autor:
Ashfaq Chauhan, Upma Chitkara, Ramya Walsan, Ursula M. Sansom-Daly, Elizabeth Manias, Davinia Seah, Angie Dalli, Nadine El-Kabbout, Thit Tieu, Mashreka Sarwar, Misbah Faiz, Nancy Huang, Vitor Moraes Rocha, Abhijit Pal, Reema Harrison
Publikováno v:
BMC Palliative Care, Vol 23, Iss 1, Pp 1-11 (2024)
Abstract Background Advance care planning (ACP) describes the process of supporting individuals at any age or stage of health to consider and share their personal values, life goals, and preferences regarding future health care. Engaging in ACP is as
Externí odkaz:
https://doaj.org/article/6cb44ee3d1a3452189bd2ec9ed00528a
Speech to text models tend to be trained and evaluated against a single target accent. This is especially true for English for which native speakers from the United States became the main benchmark. In this work, we are going to show how two simple m
Externí odkaz:
http://arxiv.org/abs/2212.12048
Autor:
Pandey, Laxmi, Paul, Debjyoti, Chitkara, Pooja, Pang, Yutong, Zhang, Xuedong, Schubert, Kjell, Chou, Mark, Liu, Shu, Saraf, Yatharth
Inverse text normalization (ITN) is used to convert the spoken form output of an automatic speech recognition (ASR) system to a written form. Traditional handcrafted ITN rules can be complex to transcribe and maintain. Meanwhile neural modeling appro
Externí odkaz:
http://arxiv.org/abs/2207.09674
Autor:
Reema Harrison, Maha Pervaz Iqbal, Upma Chitkara, Corey Adams, Ashfaq Chauhan, Rebecca Mitchell, Elizabeth Manias, Megan Alston, Anne Marie Hadley
Publikováno v:
International Journal for Equity in Health, Vol 23, Iss 1, Pp 1-74 (2024)
Abstract Background Patient-reported experience measures (PREMs) are used to drive and evaluate unit and organisational-level healthcare improvement, but also at a population level, these measures can be key indicators of healthcare quality. Current
Externí odkaz:
https://doaj.org/article/1e3ec376e5c645a6899b6541fa57cb49
Autor:
Akshit Chitkara, Nirmaljot Kaur, Aditya Desai, Devanshi Mehta, Fnu Anamika, Srawani Sarkar, Nandini Gowda, Prabhdeep Sethi, Rajat Thawani, Emerson Y. Chen
Publikováno v:
Cancer Medicine, Vol 12, Iss 24, Pp 21579-21591 (2023)
Abstract Background Guidelines show that for metastatic colorectal cancer (mCRC), a combination of three‐drug regimens, fluorouracil, leucovorin, and oxaliplatin and bevacizumab (BVZ), is one of the first‐line standard therapies. BVZ is generally
Externí odkaz:
https://doaj.org/article/5e4514c1cdef4a6a99e4646b5cda7162
Autor:
Liu, Chunxi, Picheny, Michael, Sarı, Leda, Chitkara, Pooja, Xiao, Alex, Zhang, Xiaohui, Chou, Mark, Alvarado, Andres, Hazirbas, Caner, Saraf, Yatharth
It is well known that many machine learning systems demonstrate bias towards specific groups of individuals. This problem has been studied extensively in the Facial Recognition area, but much less so in Automatic Speech Recognition (ASR). This paper
Externí odkaz:
http://arxiv.org/abs/2111.09983
Autor:
Li, Jialu, Manohar, Vimal, Chitkara, Pooja, Tjandra, Andros, Picheny, Michael, Zhang, Frank, Zhang, Xiaohui, Saraf, Yatharth
Speech recognition models often obtain degraded performance when tested on speech with unseen accents. Domain-adversarial training (DAT) and multi-task learning (MTL) are two common approaches for building accent-robust ASR models. ASR models using a
Externí odkaz:
http://arxiv.org/abs/2110.03520