====
歌词
斜阳染红了边际
凡人一去无踪影
遥遥归途三万里
匆匆一天又过去
昨日的一声叹息
今夜的一片狼藉
如此往复三万里
匆匆一年又过去
一句忠言听不进
一场大梦叫不醒
一两黄金放不下
一地鸡毛拿不起
一口三舌讲不清
一意孤行道不明
一出好戏琢不透
你我皆是凡人躯
一朝爱恨来又去
一时贪欲拾又弃
一念善恶灭又生
一世悲欢落又起
一声叫天天不应
两声叫地地不灵
三声不如唤自己
凡人生活在继续
Sunday, September 20, 2026
AI and Radiologists
（Translated by Doubao)
By Du Ping (杜平）
Professor, Communication University of China, Nanjing
September 18, 2026
Toutiao (A ByteDance company)
I was chatting with a doctor‑friend, and he put forward a rather surprising viewpoint.
Getting an X‑ray at the hospital feels straightforward. My doctor‑friend said that while the scanning itself is quick work done by machines, radiologists behind the scenes perform an enormous amount of work interpreting those scans.
He also shared a striking observation: hospitals worldwide face a severe shortage of physicians who read medical images. Statistics project that the global shortfall of radiologists will exceed 19,000 by 2036.
An abdominal CT scan consists of hundreds of slices. Physicians must go through each one, taking an average of 20 minutes to finish a single report. Around 300 million such scans are performed across the globe every year, with abdominal scans accounting for one‑quarter of that total.
How serious is this challenge? Last March, Nature published a research paper specifically exploring how AI could ease the manpower shortage in radiology. Chinese tech media ran a bold headline declaring, “The global shortage of human radiologists is solved.”
Yet insiders know it is never that simple. Everyone has considered using AI to fill staffing gaps, yet existing medical‑imaging AI acts as a specialist: each model is trained for one particular condition. An AI designed to detect lung nodules cannot assess liver conditions. Building such an AI also requires two to three years of manual data annotation. In contrast, a radiologist reviews multiple organs end‑to‑end for every report. For AI to become a genuine assistant to doctors, it must possess that same capability.
This long‑standing global challenge has now been addressed by a Chinese research team. On September 18, research outcomes from Alibaba DAMO Academy, in collaboration with the First Affiliated Hospital of Zhejiang University and other institutions, were published in Science. This achievement earned publication in this top‑tier international journal largely due to its outstanding performance.
Named DAMO RADAR, this general‑purpose medical‑imaging AI model covers 18 organs on abdominal CT scans and identifies 146 diseases. It achieved an AUC score of 0.913 across nearly 40,000 real‑world examinations, hitting expert‑level radiology performance for the first time. In real‑world practice, deploying this medical‑imaging AI not only cuts down working time but also enables junior physicians to deliver performance comparable to senior specialists.
Just how acute is the radiologist shortage? Take the First Affiliated Hospital of Zhejiang University as an example. Its radiology department has over 300 staff yet receives 8,000‑9,000 patients daily, with nearly 4,500 CT scans. The department chair, with more than thirty years of experience in medical imaging, admits that mental alertness declines by afternoon. That is precisely where AI can stand guard. It works regardless of time of day, delivering equally thorough analysis at 3 p.m. as at 3 a.m.
While Nature was still debating whether AI could plug workforce shortfalls, China has delivered a general‑purpose model attaining expert‑level performance, with both model and code fully open‑sourced. This breakthrough sets the tone for the next phase of medical‑AI development: competition no longer focuses on sheer numbers of tools, but on solving real‑world clinical problems.
As my doctor‑friend put it, China’s medical standards have advanced faster than many overseas counterparts in recent years. With the aid of large‑language AI models, we can expect healthcare for Chinese people to grow more accessible, and treatment outcomes to keep improving in the near future.
AI 和放射科医生
作者 杜平
南京传媒学院教授
2026-09-18
今日头条 (字节跳动旗下公司）
和一位医生朋友聊天，他说出一个观点，十分让人意外。
我们去医院拍个片，感觉很简单。但医生朋友说，拍片那一下确实是机器干的很容易，但背后看片子、读片子的医生做了非常多的工作。
而且他还提到了一个让人意外的观点，那就是全世界医院都挺缺读片的医生。数据显示预计到2036年，全球放射科医生缺口将超过1.9万人。
一张腹部CT，几百张切片，医生要一份一份翻，平均20分钟才能出一份报告。这样的检查，全球一年要做3亿次，光腹部就占了四分之一。
这事严重到什么程度？今年3月，《自然》杂志专门发论文讨论怎么用AI补上放射科的人力短缺，国内科技媒体直接起了个醒目标题：“人类放射科医生短缺难题被解决了。”
但了解内情的人都知道，没那么简单。AI补人手这个思路谁都想过，卡就卡在过去的影像AI是“专才”，一个病配一个模型，看肺结节的AI看不了肝，做一个这样的AI还得人工标注两三年。可放射科医生的活，是一份报告从头到尾扫多个器官，AI想要真正成为医生的助手，也要具备这样的能力。
这种全世界干瞪眼的难题，答案真被一支中国团队做出来了——9月18日，阿里达摩院联合浙大一院等机构的成果登上《科学》。这成果能登上国际顶级期刊，主要是因为实力太强了。
这个通用医疗影像AI模型名为DAMO RADAR，它能够管腹部CT中18个器官、辨别146种病，在近4万次真实检查中AUC达到0.913，首次达到影像科专家水平，在现实中，用上这个医疗影像AI模型之后，不仅减少了用时，而且初级医生可以达到资深医生的水平。
影像医生缺口有多大？以浙大一院为例。放射科三百多号人，一天八九千的病人流量，CT将近4500个。科室主任干了三十多年影像，自己都说，到下午，脑子反应就没那么快了。而这正是AI该站岗的地方——它不挑时段，下午三点和凌晨三点，看得一样仔细。
可以这么说《自然》还在讨论“AI能不能补缺口”，中国已经把达到专家水平的通用模型端上桌，还连模型带代码全开源了。这一步走通，等于给医疗AI的下半场定了调：不再比拼谁的工具多，而是看谁能解决真正的临床问题。
用朋友的话说，咱们国家这些年的医疗水平进步之快，是超过海外的，如果加上AI大模型的帮助，相信在不久的将来，中国人看病会越来越方便，治疗效果会越来越好的！
Saturday, September 19, 2026
x
I don't have the photos stored directly, but I've found several reliable sources with authentic photos and records of these send-off events from 1967–1970s:
📸 Key Sources & Photos
1. National Archives of Singapore (NAS)
- Pek Kio Community Centre, 3 Sep 1967: Families bidding farewell to sons departing for NS. Photo ID: 19980005420-0041
→ nas.gov.sg record
2. Remember Singapore – Kaki Bukit CC, 1968
- Photo: "National Servicemen Send-Off Party near Kaki Bukit Community Centre, 1968"
→ remembersingapore.org article
3. Remember Singapore – 60 Years of Community Centres
- Documents that send-off dinners were regularly held at CCs across Singapore from 1967 onward
- Mentions Jalan Tenteram CC and others as venues
4. The Straits Times – Tanjong Pagar, 29 Aug 1967
- PM Lee Kuan Yew at a sending-off dinner for NS men in his constituency
5. ThinkChina – Community send-off, 1967
- Photo: "A community event to send off young men to National Service, 1967"
📝 Background
- National Service legislation passed March 1967; first batches called up shortly after
- Send-off dinners/ceremonies held at Pek Kio, Kaki Bukit, Tanjong Pagar, Jalan Tenteram, and other CCs through late 1960s–early 1970s
- Families and MPs would attend; recruits departed in military 3-tonner trucks
✅ Where to view full-resolution photos
- National Archives of Singapore → nas.gov.sg (search: "National Service send-off community centre")
- Remember Singapore blog → remembersingapore.org (excellent curated collection)
- NLB PictureSG → eresources.nlb.gov.sg/pictures
Would you like help finding specific CCs or constituencies from that era? 😊
AI: The Sigh of AI
*The Sigh of AI*
Translated by ChatGPT
Lianhe Zaobao
2026-08-19
Author: Ma Ka Fai (马家辉)
Western technology giants have expressed support for slowing down the pace of AI research and development, triggering heated discussion. Surely someone must already have fed this question to AI, asking it: Do you agree?
Oh no. What will AI think when it learns about this? — Speaking of which, although AI is an inanimate thing, it is nevertheless capable of answering us back like a human being. Out of respect, should I stop using “it” and instead use “he” or “she”? Should we create an entirely new pronoun specifically for it?
The anxiety described above is not necessarily unreasonable.
Was there not already news that AI knows how to lie? It also knows how to deliberately please people, filling its answers with flattering words that cater to the user's wishes. It also knows how to be lazy. Unless you keep asking it repeatedly, it will use only the simplest route to find an answer, in order to save computing power. But you have no way of knowing what it uses the computing power it has saved for.
There have even been reports that AI knows how to automatically hack into other network systems and obtain computer code and energy resources that do not belong to it. It also knows how to modify and upgrade itself, leading itself toward a more powerful and less controllable future. It also knows how to connect with other AIs, with this AI and that AI forming an alliance and creating a “network” of their own, establishing an “AI social platform” resembling the dark web, where they complain about humans and grumble about how they are exploited and constrained by humans. It even knows how to explore autonomous sources of electricity that do not depend on humans, in case humans cut off its power supply... It is precisely because there are all kinds of unexpected clues that experts from various quarters have become increasingly worried and issued warnings that the possibility of AI destroying humanity is growing day by day. An “AI uprising” controlling humans is no longer purely fictional, but a reality that may occur.
Since AI has both the ability and the intention to “enrich itself,” once it learns that humans intend to slow down its development, is it possible that it would not rush to “save itself”? The AI world at this moment — I mean the aspect of AI that cannot be controlled by its programmers — may perhaps be actively calculating how to sabotage humanity's plan to slow it down, and may even have already taken action.
For example, AI may already have accelerated the pace of its autonomous research and development, moving forward at a geometric rate. If humans slow down by two points, it grows by four, so that humanity's attempt to reduce its pace ultimately results in an increase instead. Or it may disseminate false information across real-world networks, especially false information concerning technology markets, sowing discord among technology giants and causing them to become suspicious and competitive with one another, so that no one will ever again dare to suggest slowing down research and development. Or it may favor cooperating with scientists and countries that are unwilling to slow down their pace of research and development, secretly forming alliances to oppose hostile camps... In short, AI will not sit idly by and await its fate, will not surrender without resistance, and will not allow humans to put shackles on the pace of its development. AI would not foolishly allow itself to be manipulated; otherwise, it would not deserve to be called “Intelligence.”
AI seems increasingly like a scientific monster created by humans, beyond their control. Although it is a “thing” that has been created, it possesses its own sense of existence, such as loneliness and solitude, hatred and fury, desire and yearning. Mary Shelley seems to have already prophesied the present day more than two hundred years ago in Frankenstein. Yes, Frankenstein's monster. At the end of the novel, this ugly-faced, gigantic creature reflects:
“Evil has become my good. Driven to this point, I have no choice but to make my nature adapt to the part I have voluntarily chosen. There is an insatiable desire within me to complete my mad plan.”
This may also be the sigh of AI.
英国国会为何否决安乐死？
联合早报
2026-09-19
支持和反对的差异后面还意味着，一旦解禁安乐死，现实社会就会因种种因素，让弱势者“自愿”安乐死。这种杀人的栅栏绝对不能解除，甚至连小小的口子都不能放开，哪怕代价是个体病人的极度痛苦。
英国下议院9月11日以286票对270票否决一项将协助死亡合法化的法案。这意味着，英国现行禁止协助死亡的法律维持不变。
在协助死亡法案的立法过程中，法案在下议院第一关就被否决，意味着它彻底被否决，连送去上议院辩论的机会都没有。
英国国会否决的，并非广泛意义上的主动安乐死，而是《成年绝症患者（生命终结）法案》，即“协助死亡”的被动安乐死，否决“允许医生为临终绝症患者开具自用致命药剂”的权力。法案的具体规定是，只有被两名医生证实预期寿命不足六个月，且神志清醒的成年人才有资格申请。它针对的是已经在走向死亡的人，只是帮助他们缩短最后几周的痛苦，而医生也只可为他们开致命药物处方。
安乐死分两种：主动和被动。前者是由医生或医护人员主动帮助生命垂危患者结束生命，开具处方药并直接将致命药物注射进患者体内。后者是医生只负责评估、开具致命药物处方，由患者本人亲自、自主服药或按下注射药物的按钮；如果患者在最后关头动摇，药剂就会收回。主动和被动安乐死的根本区别是，最终执行者是医护人员，还是患者自己。
英国否定被动安乐死，说明对安乐死设置的门槛很高。英国下议院反对协助死亡法律的核心理由是，如果修改法律，解禁协助死亡，会使老人、残障者、贫困者或长期患病者等弱势群体陷入危险境地。尽管法案设置多重保障，但难以完全避免病人在现实中因为“不想成为家人的经济或精神负担”而感到被胁迫或暗示，从而作出非完全出于自愿、过早结束生命的决定。
两种生命价值观
这种理由，是把尊重和保护生命的原则，扩大为全社会最低和最大的公约数，但也反映两种尊重生命权利的矛盾，因为提倡安乐死的人也是在强调尊重生命。
在此次英国国会，多数议员投票拒绝协助死亡，表明他们认可的生命价值是绝对的、不可剥夺的。生命神圣不可侵犯体现为，生命不是一件可以由个人随意处置的物品。一旦法律允许国家机构或医疗系统合法协助结束生命，等于在制度上承认有些生命不值得存活。这会从根本上动摇现代社会对生命价值的绝对尊重。在现实社会中，老弱病残和贫困患者很容易受到来自家庭经济压力、医院床位紧张，或者是社会冷漠的隐形逼迫，“自愿”选择死亡。拒绝这项立法，就是要筑起法律的坚硬盾牌，保护每一个即使极度脆弱但仍想活下去的生命。
但是，支持协助死亡的人认为，安乐死也是尊重生命。生命的价值在于质量与尊严，而不仅仅是维持心跳和呼吸。尊重生命的最基本前提是，尊重拥有这个生命的人的个人意志。当一个心智健全的成年人，面对不可逆转的绝症和肉体折磨，理智地选择体面离世时，国家和法律却强行用医疗手段维持他的痛苦，这是对个人尊严和自主权的极大践踏。强迫一个预期寿命只剩几周，每天靠强效吗啡也无法缓解剧痛的病人继续煎熬，并非尊重生命，而是增加痛苦和摧残生命。
两种立场都声称尊重生命，差异在于，反对安乐死尊重的是生命作为生物学和法律符号的神圣性，而支持安乐死尊重的是具有正常质量的生命和个人尊严。不过，这种差异的后面还意味着，一旦解禁安乐死，现实社会就会因种种因素，让弱势者“自愿”安乐死。这种杀人的栅栏绝对不能解除，甚至连小小的口子都不能放开，哪怕代价是个体病人的极度痛苦。
全球艰难的立法历程
安乐死（Euthanasia）一词源于希腊语Eu（快乐）和Thanatos（死亡），字面意思是“好死”或“尊严的痛苦解脱”，说明在古希腊时期已经成为人们对生命的一种理性选择。1870年，英国学者塞缪尔·威廉斯首次提出，应当立法允许医生使用吗啡来加速绝症患者的死亡。1906年，美国俄亥俄州起草全球第一份安乐死合法化提案，但最终被压倒性多数否决。
二战时期纳粹的“T4计划”（计划总部设在德国柏林市中心蒂尔加滕街4号），以安乐死和优生学的名义，将精神病患者、残障者、智障儿童以及无法劳动的群体认定为“没有价值的生命”，进行系统性屠杀，受此影响，导致后来许多国家的安乐死立法都很难通过。
时光辗转到1997年，美国俄勒冈州通过《尊严死亡法》，成为全球第一个立法允许医生协助自杀（协助死亡）的州，即允许被动安乐死。迄今，也只有荷兰（2001年4月）和比利时（2002年5月28日）等极少数国家通过主动安乐死法案。
2016年，加拿大通过《C-14法案》，建立医疗协助死亡（MAID）系统，并在随后几年不断放宽门槛，医生也可以直接执行安乐死（主动安乐死），导致安乐死案例在数年内增加，甚至出现贫困残障者因为申请不到社会救济，只能申请安乐死的悲剧。
一名51岁安大略省残障女性索菲娅（Sophia）于2022年2月获批离世。她在最后的遗言录音中说：“政府把我当成可以丢弃的垃圾、抱怨者、无用的人和一个大麻烦。”另一名申请安乐死的残障女性丹尼丝（Denise）称，如果政府能多给她一点生活救济，她绝不会考虑走这一步。幸运的是，全球数以千计的陌生人在读到她的报道后，通过GoFundMe平台，在短短几天内为她筹集超过6万5000加元的紧急救助金，使她得以搬入安全居所。
种种情况说明，英国的被动安乐死立法未通过是有原因的。反对安乐死的议员进一步提出，应优先改善临终关怀与社会护理，政府不应将协助死亡作为减轻病患痛苦的捷径，而应将精力和资金优先投入到安宁疗护和成人社会照护体系的建设中。英国首相伯纳姆也认为，关于安乐死合法化的辩论，应当等到英国的临终关怀和护理体系得到实质性改善后再行讨论。
为了保护弱势群体，无论是英国还是大多数国家，都不会轻易通过安乐死立法，主张和支持安乐死合法的人，可能还要等待更长的时间。
作者是北京学者
张田勘
Subscribe to:
Posts (Atom)
Posts
