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Publié le 18 mai 2024

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Articles de revues sur le sujet "Tatparya in navya navya"

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Sirohi, Bhawna, Sushil Beriwal, C. S. Pramesh, Supriya Chopra, Mahesh Goel, Aju Mathew, Vikas S. Ostwal et al. « Comparison of treatment plans feasible through AI enabled multidisciplinary online tumor board solution versus NCCN-based clinical decision support system (CDSS). » Journal of Clinical Oncology 38, no 4_suppl (1 février 2020) : 816. http://dx.doi.org/10.1200/jco.2020.38.4_suppl.816.

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816 Background: Multidisciplinary tumor boards at Academic Medical Centers (AMC) maximize cancer outcomes. Guidelines based CDSS are alternatives to determine care pathways. Since 2015, 300 AMC cancer experts in USA and India use an AI enabled online tumor board solution, “NAVYA,” to scale low cost access to multidisciplinary expertise, on 1-2 minutes of expert time per decision (ASCO 2017). Methods: GI patients who used NAVYA between 5/1/15-8/31/19 were analyzed. Actionable treatment plans generated by NAVYA were compared to NCCN. Actionable treatment plans include chemotherapy protocols (doses, frequencies), radiation protocols (sites, fractions), etc. Inactionable specialty level decisions (CT-RT vs. surgery) lack specificity. Results: 1302 patients (4638 treatment decisions) were analyzed: 61% (794) male, 80% between age 45 to 75, mostly with Colon, Pancreas, Gallbladder, Rectum, or Stomach cancer; 49.7% non-metastatic. Cohort was comparable to GLOBOCAN estimates. In 82.2% (3812/4638) decisions, NAVYA added value beyond NCCN. First, in 4.5% (212/4638), NAVYA recommended a patient-specific treatment plan that was not part of NCCN. Second, in 3.2% (148/4638), NAVYA recommended treatments plan for clinical scenarios not covered by NCCN, (for eg. 3rd line therapies). Third, in 74.5% (3452/4638), NAVYA used patient specific criteria including resource constraints and patient preference to choose a treatment plan amongst the multiple pathways provided by NCCN and added actionable treatment details. Conclusions: Guideline based CDSS are insufficient to make the vast majority of actionable treatment decisions. Scaling rapid access to multidisciplinary experts is critical. Leapfrogging existing guidelines based CDSS, NAVYA online tumor board makes actionable expert treatment plans possible at a large scale.
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Pramesh, C. S., Bhawna Sirohi, Shona Milon Nag, Sudeep Gupta, Benjamin O. Anderson, Nancy Renee Feldman, Premal H. Thaker, Sushil Beriwal et Rajendra A. Badwe. « Prospective study of an AI enabled online intervention to increase delivery of guideline compliant cancer care, on the ground. » Journal of Clinical Oncology 38, no 15_suppl (20 mai 2020) : 2011. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.2011.

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2011 Background: Despite survival benefits of guideline compliant cancer care, under treatment and over treatment are prevalent. Navya is an AI enabled online intervention that matches a patient’s medical record with NCCN and NCG guidelines (National Cancer Grid, India) and layers live multidisciplinary expert review to recommend actionable treatment plans. It was developed to standardize care and mitigate morbidity and mortality, by delivering on-t ime, guideline based expert treatment plans. Methods: From July 2019 to January 2020, all patients who received a Navya treatment plan based on guidelines and live expert review were included. Intended treatment plans were prospectively collected from the patient. Compliance of intended plans with NCCN (including Resource Stratified Framework) or NCG was measured. Noncompliant intended plans were categorized as overtreatment or undertreatment. After delivery of Navya plan, prospective phone follow up assessed whether noncompliant intended plans were changed to guideline compliant care. Results: Of 1707 consecutive patients who received a Navya plan, 1549 intended plans were available. Patients were diverse with respect to geographic, socioeconomic, and primary tumor distribution: West of India: 28%, North: 26%, East: 21%, South: 15%, Central: 7%, International: 3%; 35% of patients with income < $300/month; GI: 23%, Breast: 14%, Head & Neck: 11%, Thoracic: 10%. Of the 1549 intended plans, 441 (28.47% (95% CI ± 0.26%)) were not compliant with NCCN or NCG. Undertreatment was 35%, overtreatment 26%, incomplete staging workup 28% and 11% could not be categorized. Of 441 patients with noncompliant intended plans, 80.19% (± 0.97%) shared the Navya plan with their treating oncologists and 50.40% (± 0.88%) changed their intended plan to receive the Navya treatment plan. Intervention with Navya increased on-the -ground guideline compliance by ~15% (from 71.53% ±0.42% to 85.87% ± 1.73%). Conclusions: Guideline compliant care ensures best achievable clinical outcomes with existing therapies. A technological earthshot that significantly increases adoption of guideline based care is the first step towards cancer moonshots.
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Burton, Jim. « Diagrams for Navya-Nyāya ». Journal of Indian Philosophy 48, no 2 (31 janvier 2020) : 229–54. http://dx.doi.org/10.1007/s10781-020-09419-0.

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Chatterjee, Amita. « Computational Traits in Navya-Nyāya ? » Sophia 55, no 4 (3 novembre 2016) : 543–51. http://dx.doi.org/10.1007/s11841-016-0557-6.

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Rai, A. K. « Paksat ? in Navya-ny?ya ». Journal of Indian Philosophy 23, no 1 (mars 1995) : 1–8. http://dx.doi.org/10.1007/bf01062063.

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Joshi, Shalaka P., Lakshmi Ramarajan, Ojas Deshpande, Elizabeth Fernandes, Vaibhav Vanmali, Rohini W. Hawaldar, Sadhana Kannan et al. « A randomized controlled trial of a self-administered, online decision-aid (“Navya Patient Preference Tool”) to reduce decisional conflict in women with early breast cancer. » Journal of Clinical Oncology 38, no 15_suppl (20 mai 2020) : 7033. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.7033.

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7033 Background: Shared decision making to confront choices with clinical equipoise, has been the privilege of those patients with access to time intensive consults with oncologists. We conducted a randomized controlled trial for breast cancer patients to use an online, self-administered, out-of-the-medical-encounter decision aid (DA) to choose between breast conserving surgery (BCS) and mastectomy. Methods: Navya Patient Preference Tool (Navya PPT) is a multilingual DA based on adaptive conjoint analysis of tradeoffs between cost, adverse effects of radiation, and breast conservation. Prior analysis established high internal reliability and external validity of the Navya PPT. Eligible cT1/2, cN0 breast cancer patients planned for surgery were block randomized, in 1:1:1 ratio, to receive the research questionnaire (RQ) to measure decisional conflict on choice of surgery (control, arm 1), Navya PPT followed by RQ (experimental, arm 2) or Navya PPT followed by RQ administered with key male family member (experimental, arm 3). Groups were stratified with respect to age, socio-economic status (SES) and educational level. The study was powered to detect a decrease in Decisional Conflict Index (DCI) by 0.25 (β-0.8, two sided α- 0.01). Results: Between June 2017 and December 2019, 247/255 patients were randomized to arm 1 (83), arm 2 (84), and arm 3 (80). Median age was 48 years (IQR 23-76), and median pT size was .5 cm (0.5-6 cm). 59% of patients were middle or lower SES and 46.2% had ≤ 12th grade education. DCI was significantly reduced in arm 2 as compared with arm 1 (1.34 vs. 1.65, Cohen’s d 0.49 (± 0.31) p<0.05) as well as in arm 3 as compared with arm 1 (1.30 vs. 1.65, Cohen’s d 0.54 (± 0.31) p<0.05). 80% (± 6%) of patients underwent surgery of choice as determined by Navya PPT. BCS rate was similar in all three arms (85.2, 88.9 and 86.5% respectively (p=0.779). Conclusions: Online, self-administered, adaptive DAs used out of the medical encounter can reduce decisional conflict and increase access to shared decision making for every patient; especially in practices with low doctor to patient ratios. Clinical trial information: IEC/0116/1619/001 .
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Badwe, RA, Premal Thaker, Farzana Begum, Mayukh Acherjee, Gitika Srivastava, Naresh Ramarajan, Shona Nag et al. « Abstract PO4-10-10 : NAVYA-AI enabled intervention to increase real-world guideline compliant care : Improving NGS testing in breast cancer ». Cancer Research 84, no 9_Supplement (2 mai 2024) : PO4–10–10—PO4–10–10. http://dx.doi.org/10.1158/1538-7445.sabcs23-po4-10-10.

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Abstract BACKGROUND: Navya-AI is a validated online cancer informatics solution that combines artificial intelligence based analysis of the guidelines and evidence, along with asynchronous expert review. Navya-AI releases preliminary system-generated opinions for patients whose treatment plans fit high confidence based on NCCN Guidelines and prior expert reviews. Prior research (SABCS 2014-2018 and ASCO 2021 showed: 1) 97% concordance of Navya-AI predictions with an academic medical center in India and in the US 2) 80% of patients implement treatment concordant with Navya-AI recommendations on the ground 3) Navya’s NCCN and evidence-based treatment plans reduce the patient waiting times for an expert opinion by an average by 3.5 days. Next generation sequencing (NGS) is an expensive but necessary method for identifying patients for risk reduction and therapy selection in breast cancer (BC). NGS testing can be over-used or under-used, and compliance with NCCN guidelines on patient selection is especially important in resource-constrained settings and Low Middle Income Countries (LMIC) such as India. The aim of this study is to find the physician compliance to NCCN guidelines on NGS testing in India, and how Navya-AI can identify the opportunity for improved care, and improve compliance with guidelines for optimal care. METHODS: From January 2022 to May 2023, Breast Cancer patients receiving Navya-AI treatment plan (based on guidelines and live expert-review) were analyzed. Patients who could afford NGS testing and targeted therapies, and who met the Enhanced tier of NCCN resource stratified guidelines for their care centers were identified. Their records were screened by Navya-AI to assess if they met NCCN criteria for NGS testing for risk reduction or for treatment selection (young age, positive family history, triple negative breast cancer etc.). Treating physicians were then analyzed if they had ordered NGS appropriately, or had missed an opportunity for NGS (undertreatment), or had over-ordered NGS (overtreatment).RESULTS: 521 BC patients who could afford NGS tests received a Navya-AI plan during this period. Of these, 85% were Indian patients (415/521) and were analyzed. Patients were diverse with respect to age,cancer stage, family history of cancer and histology: Age &lt; 35: 6.7%, 35-50: 33%, 51-65: 43.76%, &gt;65: 16.51%; early stage: 21.5%, locally advanced stage: 29.56%,metastatic stage: 47.79% and benign disease: 1%; positive family history of cancer: 37.35%, triple negative BC: 21.9%. Of 415 indian breast cancer patients who could afford testing, NGS testing was indicated in 69.64% (289/415) as per NCCN guidelines. The treating physician was compliant with NCCN guidelines in only 47.95% (199/415) of the cases: 19.2% (80/415) of the time, NGS was indicated and the treating physician ordered the same; 28.67% (119/415) of the time, NGS was not indicated, and the treating physician did not order NGS. The remaining 52% were not compliant with NCCN. Under-treatment was present in 50.36% (209/415) of cases, and was the vast majority of fallouts. Over-treatment was only present in 1.69% (7/415). In all 50.63% (209/415) cases, where NGS was not ordered by the treating oncologist, but was indicated, and affordable to the patient, Navya requested the patient to discuss the risks/benefits of NGS testing with their treating oncologist. CONCLUSION: NGS testing in BC patients has significant impact on risk-reduction, genetic counseling, choice of surgery, and treatment options for adjuvant therapy. Missed opportunities for NGS testing in more than 50% of the patients who can afford the testing and resultant therapies, points to a signficant area where compliance with guidelines and expert opinions can impact outcomes. A 'Technological Earthshot" that significantly increases adoption of guideline-based care is the first and an easy step towards 'Cancer Moonshots'. Citation Format: RA Badwe, Premal Thaker, Farzana Begum, Mayukh Acherjee, Gitika Srivastava, Naresh Ramarajan, Shona Nag, Sudeep Gupta, Seema Gulia, Jaya Ghosh, Bhawna Sirohi. NAVYA-AI enabled intervention to increase real-world guideline compliant care: Improving NGS testing in breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-10-10.
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Basavaraju, Navya, Annamarie Jones et Probal K. Moulik. « Artificial Pancreas – Hybrid Closed Loop : an impending revolution ». Independent Nurse 2024, no 4 (2 avril 2024) : 12–18. http://dx.doi.org/10.12968/indn.2024.4.12.

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Wada, Toshihiro. « Qualifier (visesana) in Navya-nyaya Philosophy ». JOURNAL OF INDIAN AND BUDDHIST STUDIES (INDOGAKU BUKKYOGAKU KENKYU) 37, no 1 (1988) : 506–0. http://dx.doi.org/10.4259/ibk.37.506.

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Ramarajan, Naresh, Farzana Begum et Gitika Srivastava. « BIO19-022 : Reducing Patient Waiting Times for Treatment Decision Making, Helps in Improving the Treatment Planning Process ». Journal of the National Comprehensive Cancer Network 17, no 3.5 (8 mars 2019) : BIO19–022. http://dx.doi.org/10.6004/jnccn.2018.7254.

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Background: Availability of care is an important characteristic of effective primary healthcare systems. Imbalanced oncologist to patient ratios (∼1600: 1.8 M in India, ∼23,000: 15 M in USA), impedes access to expertise. On average it takes a week or more to get an online expert review from leading cancer hospitals in the United States and in India. Such delays have an important psychosocial impact on the patient and caregivers. Patients worldwide often race to start treatments at non-expert centers and may experience worse health outcomes from lack of expert tumor board review of their cases. This study aimed to examine the impact of Navya, a health services technology, on reducing the patient wait time in real-time treatment decision making. Methods: Navya generates personalized treatment plans that maps 98.8% within NCCN Resource Stratified Guidelines [SABCS 2017, NCCN 2018]. This is vetted on mobile by oncologists at tertiary centers like TMC NCG to provide expert opinion reports to patients. Since 2015, approximately 25,775 patients from 60 countries have reached out for an online opinion. On the ground, 78% of patients received evidence-based treatments recommended by Navya [ASCO 2017]. The Navya system releases preliminary system-generated opinions for patients whose treatment plans fit high confidence based on NCCN Guidelines and prior expert reviews. The mean reduction in time between a system-generated opinion and an expert-reviewed opinion was studied in a prospective cohort of patients between July 1, 2017, and August 30, 2018. Results: 313 patients received a system-generated treatment plan in the study period. Only approximately 10% of these plans were modified by experts to add additional treatment details since these were cases with high confidence in treatment decision-making. Navya delivered a preliminary treatment plan on an average of 86 hours (SD, 153 hours) prior to the expert response time. Of the 313 patients studied, 44% of patients would have waited an additional 3 days longer to receive an expert-reviewed recommendation. Conclusions: Navya’s NCCN and evidence-based treatment plans reduce the patient waiting times for an expert opinion average by 86 hours. This rapid confirmation of the right treatment plan at the time of patient need has potential to relieve patient anxieties at critical junctures in treatment decision-making and helps improve the treatment-planning process.
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Thèses sur le sujet "Tatparya in navya navya"

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Bhattacharjy, Nayana. « The Concept of tatparya in navya navya : some philosophical problems ». Thesis, University of North Bengal, 2007. http://hdl.handle.net/123456789/75.

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Wada, Toshihiro. « Invariable concomitance in Navya-Nyāya / ». Delhi : Sri Satguru publ, 1990. http://catalogue.bnf.fr/ark:/12148/cb357493212.

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WADA, Toshihiro. « Delimitor (Avacchedaka) in Navya-Nyāya Philosophy (1) ». 名古屋大学文学部, 1988. http://hdl.handle.net/2237/9120.

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Chakraborty, Riki. « Some problems concerning Nirvikalpaka pratyaksa in navya nyaya : a critical study ». Thesis, University of North Bengal, 2009. http://hdl.handle.net/123456789/94.

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Choudhury, Indrani. « 'Will-Generated Cognition' In Indian philosophy with special reference to Navya Nyaya ». Thesis, University of North Bengal, 2021. http://ir.nbu.ac.in/handle/123456789/4757.

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Gerschheimer, Gerdi. « La theorie de la signification dans le navya-nyaya : le saktivadavicara de gadadhara (17e siecle) ». Paris 3, 1993. http://www.theses.fr/1993PA030079.

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Le saktivadavicara - "examen des theories de la sakti (capacite) expressive d'un mot)" -, un classique sanskrit de la semantique elaboree par le navay-nyaya, est connu de nos jours dans une version dont l'authenticite n'avait pas ete mise en doute. Au terme d'une nouvelle edition de la premiere partie du texte (fondee sur 20 manuscrits et 7 editions), accompagnee d'une traduction commentee, cette version vulgate apparait comme le resultat de nombreuses transformations d'un texte proche d'une version courte reconstituee a partie de quatre manuscrits
The saktivadavicara - "enquiry into the theories of sakti (expressive capacity of a word)" - is one of the main sanskrit navya-nayayika texts dealing with semantics. It is nowadays widely known in a version whose authenticity had not been questioned. A new edition of the first art of the text (on the basis of 20 manuscripts and 7 editions), together with an annotated translation, shows that this version is the result of many alterations of a text which was close to a shorter version, reconstituted with the help of four manuscripts
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和田, 壽弘. « 初期新ニヤーヤ学派における言語哲学の基礎的研究 ». 2006. http://hdl.handle.net/2237/13138.

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Livres sur le sujet "Tatparya in navya navya"

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Rāmacandraṃ, Icchāpurapu. Navya. Vijayavāḍa : Navajyōti Pablikēṣans, 1992.

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Gokak, Vinayak Krishna. Navya kāvya. Beṅgaḷūru : Aibiec Prakāśana, 1988.

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Jaganāthaśarma, E. En. Navya nīrājanaṃ : Navya neerajanam : 50 kathalu, kathakula antaraṅgālu. Guṇṭūru : Amarāvati Pablikēṣans, 2013.

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Dēsāyi, Śāntinātha. Navya sāhitya darśana. Śivamogga : Parisara Sāhitya Prakāśana, 1990.

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Ānand, Vārāla. Navya citra vaitāḷikulu. [Karimnagar] : Philiṃ Phauṇḍēṣan, 1998.

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Dēsāyi, Śāntinātha. Navya sāhitya darśana. Beṅgaḷūru : Sapna Buk Haus, 2004.

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Nāḍiga, Sumatīndra. Aḍigaru mattu navya kāvya. Beṅgaḷūru : Esbies Pabliṣars Ḍisṭribyūṭars, 1997.

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Bhadrayya, Immaḍōju. Navya kavitvaṃlō bhāvakavitvaṃ viślēṣaṇa. [Hyderabad] : Copies available with, Kinnera Publications, 1999.

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Sangambo, Charity. Vihande vyamuMeheba navya muAngola. Lusaka, Zambia : Panos Southern Africa, 1999.

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Urvaśī : Eka navya nikasha. Dillī : Mīnākshī Prakāśana, 2011.

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Chapitres de livres sur le sujet "Tatparya in navya navya"

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Sastry, O. G. P. Kalyana. « Technical Language of Navya Nyāya ». Dans Handbook of Logical Thought in India, 657–79. New Delhi : Springer India, 2022. http://dx.doi.org/10.1007/978-81-322-2577-5_19.

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Sastry, O. G. P. Kalyana. « Technical Language of Navya Nyāya ». Dans Handbook of Logical Thought in India, 1–23. New Delhi : Springer India, 2022. http://dx.doi.org/10.1007/978-81-322-1812-8_19-1.

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Matilal, Bimal Krishna. « Awareness and Meaning in Navya-Nyāya ». Dans Analytical Philosophy in Comparative Perspective, 373–91. Dordrecht : Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-6499-0_16.

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Bhattacharya, S. « Abstraction, Analysis and Universals : The Navya-Nyāya Theory ». Dans Analytical Philosophy in Comparative Perspective, 189–202. Dordrecht : Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-6499-0_9.

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Burton, Jim, Lopamudra Choudhury et Mihir Chakraborty. « A Survey and Evaluation of Diagrams for Navya-Nyāya ». Dans Diagrammatic Representation and Inference, 280–95. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91376-6_27.

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Venkataramana, B. V. « Influence of Navya-Nyāya Concepts and Language in Vyākaraṇa ». Dans Handbook of Logical Thought in India, 633–55. New Delhi : Springer India, 2022. http://dx.doi.org/10.1007/978-81-322-2577-5_20.

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Venkataramana, B. V. « Influence of Navya-Nyāya Concepts and Language in Vyākaraṇa ». Dans Handbook of Logical Thought in India, 1–23. New Delhi : Springer India, 2021. http://dx.doi.org/10.1007/978-81-322-1812-8_20-1.

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Ghosh, Raghunath. « Tatparya and its role in verbal understanding ». Dans The Paideia Archive : Twentieth World Congress of Philosophy, 41–48. Philosophy Documentation Center, 1998. http://dx.doi.org/10.5840/wcp20-paideia199824416.

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I examine the concept of intention (tatparya) and its role in the phenomenon of verbal comprehension (sabdabodha) with special reference to Navya Nyaya, followed by some critical and evaluative remarks. An effort has been made to give an account of the apprehension of intention (tatparya) in four types of sentences: a) the ambiguous sentence b) the non-ambiguous sentence c) the vedic sentence and d) the sentence uttered by a parrot.
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Fleming, Christopher T. « The Bhāṭṭa School of Benares ». Dans Ownership and Inheritance in Sanskrit Jurisprudence, 115–57. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198852377.003.0004.

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This chapter examines the reception of Dāyabhāga-centred, Gauḍa jurisprudence and Navya-Nyāya theories of ownership in the Dharmaśāstra and Mīmāṃsā writings of the Bhaṭṭa family of Mahārāṣṭrian Deśastha brāhmaṇas who led the southern (Dākṣinātya) community of paṇḍitas in Vārāṇasī between the sixteenth and seventeenth centuries. The Bhaṭṭas’ polemic against the Navadvīpan, Navya-Nyāya-inflected school of jurisprudence marks a watershed moment when the Mitākṣarā and its Mīmāṃsā-derived theory of ownership were incorporated into a broader, distinctively southern scale of Dharmaśāstra texts that framed the Mitākṣarā/Dāyabhāga divide as a debate between Mīmāṃsā and Navya-Nyāya theories of property. By the close of the seventeenth century, one could speak of two complex, comprehensive schools of Dharmaśāstric thought, inflected by Mīmāṃsā and Navya-Nyāya philosophy, centred around pedagogical networks in Vārāṇasī and Navadvīpa, taking paradigmatically divergent approaches to the problem of inheritance, and emanating from commentarial literature on the Mitākṣarā and Dāyabhāga respectively.
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« Some Aspects of the Navya-Nyāya Theory of Inference (1987) ». Dans Indian Logic, 170–90. Routledge, 2013. http://dx.doi.org/10.4324/9780203037119-15.

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