[病人被撕成碎片]

Q3 Medicine Recenti progressi in medicina Pub Date : 2024-04-01 DOI:10.1701/4246.42228
Lorenzo Farina
{"title":"[病人被撕成碎片]","authors":"Lorenzo Farina","doi":"10.1701/4246.42228","DOIUrl":null,"url":null,"abstract":"<p><p>Dissecting bodies is a common practice in many cultures. But in \"big data medicine\", the art of dissecting the human body has become an obsession. Indeed, modern biotechnology allows us to see and measure the molecular components of every single cell. But how can we put this immense number of bits and pieces back together again and see the patient as a whole? The first turning point is that proposed by René Descartes, who, inspired by dreams and visions, conceived the idea of unifying all scientific disciplines through the pervasive application of mathematics. Descartes formulates four basic rules, the second (top-down method) and third (bottom-up method) of which become crucial in modern data analysis. An instructive case study considered here is that of pulmonary tuberculosis, where the Cartesian approach of decomposing problems into smaller and smaller \"pieces\" - from organism to organ and from cellular lesion to the microscopic level - has led to the cure of the disease through antibiotics. This success story inspired Paul Ehrlich who, with the concept of the \"magic bullet\", defined modern pharmacology. However, this paradigm is being challenged today by multifactorial diseases and big data medicine, where the enormous availability of clinical and molecular data must be integrated to arrive at a therapeutic decision. The Cartesian approach shows its limitations today, as witnessed by the similar difficulty in fields other than medicine, illustrated here by the case of choosing to produce a successful television series based on user profiling. The take-home message is that the amount of data collected does not automatically guarantee success but that, instead of being data-driven, a collective \"human\" overview and assessment is inevitable. That is, close collaboration between clinicians and data analysts, integrating expertise, is needed to address challenges in the diagnosis and treatment of complex diseases through imagination and not mere extrapolation.</p>","PeriodicalId":20887,"journal":{"name":"Recenti progressi in medicina","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[Patients torn to pieces.]\",\"authors\":\"Lorenzo Farina\",\"doi\":\"10.1701/4246.42228\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Dissecting bodies is a common practice in many cultures. But in \\\"big data medicine\\\", the art of dissecting the human body has become an obsession. Indeed, modern biotechnology allows us to see and measure the molecular components of every single cell. But how can we put this immense number of bits and pieces back together again and see the patient as a whole? The first turning point is that proposed by René Descartes, who, inspired by dreams and visions, conceived the idea of unifying all scientific disciplines through the pervasive application of mathematics. Descartes formulates four basic rules, the second (top-down method) and third (bottom-up method) of which become crucial in modern data analysis. An instructive case study considered here is that of pulmonary tuberculosis, where the Cartesian approach of decomposing problems into smaller and smaller \\\"pieces\\\" - from organism to organ and from cellular lesion to the microscopic level - has led to the cure of the disease through antibiotics. This success story inspired Paul Ehrlich who, with the concept of the \\\"magic bullet\\\", defined modern pharmacology. However, this paradigm is being challenged today by multifactorial diseases and big data medicine, where the enormous availability of clinical and molecular data must be integrated to arrive at a therapeutic decision. The Cartesian approach shows its limitations today, as witnessed by the similar difficulty in fields other than medicine, illustrated here by the case of choosing to produce a successful television series based on user profiling. The take-home message is that the amount of data collected does not automatically guarantee success but that, instead of being data-driven, a collective \\\"human\\\" overview and assessment is inevitable. That is, close collaboration between clinicians and data analysts, integrating expertise, is needed to address challenges in the diagnosis and treatment of complex diseases through imagination and not mere extrapolation.</p>\",\"PeriodicalId\":20887,\"journal\":{\"name\":\"Recenti progressi in medicina\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Recenti progressi in medicina\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1701/4246.42228\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Recenti progressi in medicina","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1701/4246.42228","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0

摘要

在许多文化中,解剖人体是一种常见的做法。但在 "大数据医学 "中,解剖人体的艺术已成为一种痴迷。的确,现代生物技术让我们能够看到并测量每个细胞的分子成分。但是,我们如何才能将这些数量庞大的碎片重新组合在一起,并将患者视为一个整体呢?第一个转折点是勒内-笛卡尔(René Descartes)提出的,他在梦想和幻觉的启发下,构想出通过数学的普遍应用来统一所有科学学科。笛卡尔提出了四条基本规则,其中第二条(自上而下法)和第三条(自下而上法)在现代数据分析中至关重要。笛卡尔将问题分解成越来越小的 "碎片"--从机体到器官,从细胞病变到微观层面--从而通过抗生素治愈了这种疾病。这个成功的故事启发了保罗-埃利希,他提出了 "神奇子弹 "的概念,定义了现代药理学。然而,这一范式如今正受到多因素疾病和大数据医学的挑战,必须整合大量可用的临床和分子数据,才能做出治疗决定。笛卡尔式方法如今已显示出其局限性,医学以外的其他领域也面临着类似的困难,这里以根据用户特征分析选择制作一部成功的电视剧为例加以说明。这给我们带来的启示是,收集到的数据量并不能自动保证成功,与其说是数据驱动,不如说是 "人 "的集体概述和评估是不可避免的。也就是说,临床医生和数据分析师之间需要紧密合作,整合专业知识,通过想象而不仅仅是推断来应对复杂疾病诊断和治疗方面的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
[Patients torn to pieces.]

Dissecting bodies is a common practice in many cultures. But in "big data medicine", the art of dissecting the human body has become an obsession. Indeed, modern biotechnology allows us to see and measure the molecular components of every single cell. But how can we put this immense number of bits and pieces back together again and see the patient as a whole? The first turning point is that proposed by René Descartes, who, inspired by dreams and visions, conceived the idea of unifying all scientific disciplines through the pervasive application of mathematics. Descartes formulates four basic rules, the second (top-down method) and third (bottom-up method) of which become crucial in modern data analysis. An instructive case study considered here is that of pulmonary tuberculosis, where the Cartesian approach of decomposing problems into smaller and smaller "pieces" - from organism to organ and from cellular lesion to the microscopic level - has led to the cure of the disease through antibiotics. This success story inspired Paul Ehrlich who, with the concept of the "magic bullet", defined modern pharmacology. However, this paradigm is being challenged today by multifactorial diseases and big data medicine, where the enormous availability of clinical and molecular data must be integrated to arrive at a therapeutic decision. The Cartesian approach shows its limitations today, as witnessed by the similar difficulty in fields other than medicine, illustrated here by the case of choosing to produce a successful television series based on user profiling. The take-home message is that the amount of data collected does not automatically guarantee success but that, instead of being data-driven, a collective "human" overview and assessment is inevitable. That is, close collaboration between clinicians and data analysts, integrating expertise, is needed to address challenges in the diagnosis and treatment of complex diseases through imagination and not mere extrapolation.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Recenti progressi in medicina
Recenti progressi in medicina Medicine-Medicine (all)
CiteScore
0.90
自引率
0.00%
发文量
143
期刊介绍: Giunta ormai al sessantesimo anno, Recenti Progressi in Medicina continua a costituire un sicuro punto di riferimento ed uno strumento di lavoro fondamentale per l"ampliamento dell"orizzonte culturale del medico italiano. Recenti Progressi in Medicina è una rivista di medicina interna. Ciò significa il recupero di un"ottica globale e integrata, idonea ad evitare sia i particolarismi della informazione specialistica sia la frammentazione di quella generalista.
期刊最新文献
[Clinical management of a patient with non-triple-negative breast cancer who converts to a triple-negative subtype at recurrence.] Twelve tips for medical teachers to facilitate effective discussion among students to engage in reflective interpretation of Museum Arts [Effectiveness and tolerability of sacituzumab govitecan in elderly patient with advanced triple negative breast cancer.] [Efficacy of topical tirbanibulin in treating grade 2 actinic keratosis.] [Expertise or talent: what is more important in a doctor?]
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1